当前位置：文档之家› ASHRAE Whitepaper - 2011 数据处理环境散热指南

ASHRAE Whitepaper - 2011 数据处理环境散热指南

ASHRAE TC 9.9 2011 Thermal Guidelines for Data Processing Environments – Expanded Data Center Classes and Usage Guidance
Whitepaper prepared by ASHRAE Technical Committee (TC) 9.9 Mission Critical Facilities, Technology Spaces, and Electronic Equipment
This ASHRAE white paper on data center environmental guidelines was developed by members of the TC 9.9 committee representing the IT equipment manufacturers and submitted to the voting members of TC 9.9 for review and approval. In this document the term ‘server’ is used to generically describe any IT equipment (ITE) such as servers, storage, network products, etc. used in data-center-like applications.
Executive Summary
ASHRAE TC 9.9 created the first edition of the ‘Thermal Guidelines for Data Processing Environments’ in 2004. Prior to that the environmental parameters necessary to operate data centers were anecdotal or specific to each IT manufacturer. In the second edition of the Thermal Guidelines in 2008 ASHRAE TC 9.9 expanded the environmental range for data centers so that an increasing number of locations throughout the world were able to operate with more hours of economizer usage. At the time of the first Thermal Guidelines the most important goal was to create a common set of environmental guidelines that IT equipment would be designed to meet. Although computing efficiency was important, performance and availability took precedence when creating the guidelines and temperature and humidity limits were set accordingly. Progressing through the first decade of the 21st century, increased emphasis has been placed on computing efficiency. Power usage effectiveness (PUE) has become the new metric to measure data center efficiency which creates a measurable way to see the effect of data center design and operation on data center efficiency. To improve PUE air- and water-side economization have become more commonplace with a drive to use them year-round. To enable improved PUE capability TC 9.9 has created additional environmental classes along with guidance on the usage of the existing and new classes. Expanding the capability of IT equipment to meet wider environmental requirements can change reliability, power consumption and performance capabilities of the IT equipment and guidelines are provided herein on how these aspects are affected. From the second edition (2008) of the thermal guidelines the purpose of the recommended envelope was to give guidance to data center operators on maintaining high reliability and also operating their data centers in the most energy efficient manner. This envelope was created for general use across all types of businesses and conditions. However, different environmental envelopes may be more appropriate for different business values and climate conditions. Therefore, to allow for the potential to operate in a different envelope that might provide even greater energy savings, this whitepaper provides general guidance on server metrics that will assist data center operators in creating a different operating envelope that matches their business values. Each of these metrics is described herein, with more details to be provided in the upcoming third ? 2011 American Society of Heating, Refrigerating and Air-Conditioning Engineers, Inc. All rights reserved. 2

edition of the “Thermal Guidelines for Data Processing Environments” Datacom Book. Any choice outside of the recommended region will be a balance between the additional energy savings of the cooling system versus the deleterious effects that may be created in reliability, acoustics, or performance. A simple representation of this process is shown in Figure 1 below for those who decide to create their own envelope and not use the recommended envelope for operation of their data center.
Figure 1.Server Metrics for Determining Data Center Operating Environmental Envelope A flow chart is also provided to help guide the user through the appropriate evaluation steps. Many of these metrics center around simple graphs that describe the trends. However, the use of these metrics is intended for those that plan to go beyond the recommended envelope for additional energy savings. The use of these metrics will require significant additional analysis to understand the TCO impact of operating beyond the recommended envelope. The other major change in the environmental specification is in the data center classes. Previously there were two classes applying to ITE used in data center applications: Classes 1 and 2. The new environmental guidelines have more data center classes to accommodate different applications and priorities of IT equipment operation. This is critical because a single data center class forces a single optimization whereas each data center needs to be optimized based on the operator’s own optimization criteria (e.g. fulltime economizer use versus maximum reliability).
Figure 1.Server Metrics for Determining Data Center Operating Environmental Envelope A flow chart is also provided to help guide the user through the appropriate evaluation steps. Many of these server metrics center around simple graphs that describe the trends. However, the use of these metrics is intended for those that plan to go beyond the recommended envelope for additional energy savings. To do this properly requires significant additional analysis in each of the metric areas to understand the TCO impact of operating beyond the recommended envelope. The intent of outlining the process herein is to demonstrate a methodology and provide general guidance. This paper contains generic server equipment metrics and does not necessarily represent the characteristics of any particular piece of IT equipment. For specific equipment information, contact the IT manufacturer. The other major change in the environmental specification is in the data center classes. Previously there were two classes applying to ITE used in data center applications: Classes 1 and 2. The new environmental guidelines have more data center classes to accommodate different applications and priorities of IT equipment operation. This is critical because a single data center class forces a single optimization whereas each data ? 2011 American Society of Heating, Refrigerating and Air-Conditioning Engineers, Inc. All rights reserved. 3

center needs to be optimized based on the operator’s own criteria (e.g. fulltime economizer use versus maximum reliability).
Introduction
The first initiative of TC 9.9 was to publish the book, “Thermal Guidelines for Data Processing Environments”. ? Prior to the formation of TC 9.9, each commercial IT manufacturer published its own independent temperature specification. Typical data centers were operated in a temperature range of 20 to 21°C with a common notion of ‘cold is better’. ? Most data centers deployed IT equipment from multiple vendors resulting in the ambient temperature defaulting to the IT equipment having the most stringent temperature requirement plus a safety factor. ? TC 9.9 obtained informal consensus from the major commercial IT equipment manufacturers for both “recommended” and “allowable” temperature and humidity ranges and for four environmental classes, two of which were applied to data centers. ? Another critical accomplishment of TC 9.9 was to establish IT equipment air inlets as the common measurement point for temperature and humidity compliance; requirements in any other location within the data center were optional. The global interest in expanding the temperature and humidity ranges continues to increase driven by the desire for achieving higher data center operating efficiency and lower total cost of ownership (TCO). In 2008, TC 9.9 revised the requirements for Classes 1 and 2 to be less stringent. The following table summarizes the current guidelines published in 2008 for temperature, humidity, dew point, and altitude. Table 1. ASHRAE 2008 Thermal Guidelines
Equipment Environment Specifications Product Operation a, b
Maximum Dew Point (°C) Maximum Elevation (m) Maximum Rate of Change (°C/h)
Product Power Off b, c
Dry-Bulb Temperature (°C) Relative Humidity (%) Maximum Dew Point (°C)
Dry Bulb Temperature (°C)
Class
Humidity Range, Non Condensing
Allowable Recommended Allowable (% RH) 15 to 32 d 10 to 35 d 5 to 35 d, g 5 to 40 d, g 18 to 27 e 18 to 27 e NA NA
Recommended
1 2 3 4
20 to 80 20 to 80 8 to 80 8 to 80
5.5oC DP to 60% RH and 15oC DP 5.5oC DP to 60% RH and 15oC DP NA NA
17 21 28 28
3050 3050 3050 3050
5/20 f 5 to 45 8 to 80 5/20 f 5 to 45 8 to 80 NA NA 5 to 45 8 to 80 5 to 45 8 to 80
27 27 29 29
? 2011 American Society of Heating, Refrigerating and Air-Conditioning Engineers, Inc. All rights reserved.
4

a. Product equipment is powered on. b. Tape products require a stable and more restrictive environment (similar to Class 1). Typical requirements: minimum temperature is 15°C, maximum temperature is 32°C, minimum relative humidity is 20%, maximum relative humidity is 80%, maximum dew point is 22°C, rate of change of temperature is less than 5°C/h, rate of change of humidity is less than 5% RH per hour, and no condensation. c. Product equipment is removed from original shipping container and installed but not in use, e.g., during repair maintenance, or upgrade. d. Derate maximum allowable dry-bulb temperature 1°C/300 m above 900 m. e. Derate maximum recommended dry-bulb temperature 1°C/300 m above 1800 m. f. 5°C/hr for data centers employing tape drives and 20°C/h for data centers employing disk drives. g. With diskette in the drive, the minimum temperature is 10°C.
The primary differences in the first version of the Thermal Guidelines published in 2004 and the current guidelines published in 2008 were in the changes to the recommended envelope shown in the table below. Table 2. Comparison of 2004 and 2008 Versions of Recommended Envelopes
Increasing the temperature and humidity ranges increased the opportunity to use compressor-less cooling solutions. Typically, the equipment selected for data centers is designed to meet either Class 1 or 2 requirements. Class 3 is for applications such as personal computers and Class 4 is for applications such as “point of sale” IT equipment used indoors or outdoors. These environmental guidelines / classes are really the domain and expertise of IT OEMs. TC 9.9’s “IT Subcommittee” is exclusively comprised of engineers from commercial IT manufacturers; the subcommittee is strictly technical. The commercial IT manufacturers’ design, field, and failure data is shared (to some extent) within this IT Subcommittee enabling greater levels of disclosure and ultimate decision to expand the environmental specifications. Prior to TC 9.9, there were no organizations or forums to remove the barrier of sharing information amongst competitors. This is critical since having some manufacturers conform while others do not returns one to the trap of a multi-vendor data center where the most stringent requirement plus a safety factor would most likely preside. The IT manufacturers negotiated amongst themselves in private resulting in achieving some sharing of critical information. ? 2011 American Society of Heating, Refrigerating and Air-Conditioning Engineers, Inc. All rights reserved. 5

From an end user perspective, it is also important that options are provided for multivendor facilities such as: Option 1 – use IT equipment optimized for a combination of attributes including energy efficiency and capital cost with the dominant attribute being RELIABILITY Option 2 – use IT equipment optimized for a combination of attributes including some level of reliability with the dominant attribute being ENERGY and compressorless cooling The industry needs both types of equipment but also needs to avoid having Option 2 inadvertently increase the acquisition cost of Option 1 by increasing purchasing costs through mandatory requirements NOT desired or used by all end users. Expanding the temperature and humidity ranges can increase the physical size of the IT equipment (e.g. more heat transfer area required), increase IT equipment air flow, etc. This can impact embedded energy cost, power consumption and finally the IT equipment purchase cost. TC 9.9 has demonstrated the ability to unify the commercial IT manufacturers and improve the overall performance including energy efficiency for the industry. The TC 9.9 IT Subcommittee worked diligently to expand the Environmental Classes to include two new data center classes. By adding these new classes and NOT mandating all servers conform to something such as 40°C, the increased server packaging cost for energy optimization becomes an option rather than a mandate. Developing these new classes exclusively amongst the commercial IT manufacturers should produce better results since the sharing of some critical data amongst them has proven in the past to achieve broader environmental specifications than what otherwise would have been achieved. The next version of the book, “Thermal Guidelines for Data Processing Environments, Third Edition”, will include expansion of the environmental classes as described in this whitepaper. The naming conventions have been updated to better delineate the types of IT equipment. The old and new classes are now specified differently.
? 2011 American Society of Heating, Refrigerating and Air-Conditioning Engineers, Inc. All rights reserved.
6

Table 3. 2011 and 2008 Thermal Guideline Comparisons
2011 2008 classes classes A1 1 A2 A3 A4 B 2 NA NA 3 Office, home, transportable environment, etc. Point-of-sale, industrial, factory, etc. Datacenter Applications IT Equipment Enterprise servers, storage products Volume servers, storage products, personal computers, workstations Volume servers, storage products, personal computers, workstations Volume servers, storage products, personal computers, workstations Personal computers, workstations, laptops, and printers Point-of-sale equipment, ruggedized controllers, or computers and PDAs Environmental Control Tightly controlled Some control Some control Some control Minimal control
C
4
No control
New Environmental Class Definitions Compliance with a particular environmental class requires full operation of the equipment over the entire allowable environmental range, based on non-failure conditions. Class A1: Typically a data center with tightly controlled environmental parameters (dew point, temperature, and relative humidity) and mission critical operations; types of products typically designed for this environment are enterprise servers and storage products. Class A2: Typically an information technology space or office or lab environment with some control of environmental parameters (dew point, temperature, and relative humidity); types of products typically designed for this environment are volume servers, storage products, personal computers, and workstations. Class A3/A4: Typically an information technology space or office or lab environment with some control of environmental parameters (dew point, temperature, and relative humidity); types of products typically designed for this environment are volume servers, storage products, personal computers, and workstations. Class B: Typically an office, home, or transportable environment with minimal control of environmental parameters (temperature only); types of products typically designed for this environment are personal computers, workstations, laptops, and printers. Class C: Typically a point-of-sale or light industrial or factory environment with weather protection, sufficient winter heating and ventilation; types of products typically designed for this environment are point-of-sale equipment, ruggedized controllers, or computers and PDAs.
? 2011 American Society of Heating, Refrigerating and Air-Conditioning Engineers, Inc. All rights reserved.
7

Table 4. 2011 ASHRAE Thermal Guidelines (I-P version in Appendix E)
The 2008 recommended ranges as shown here and in Table 2 can still be used for data centers. For potentially greater energy savings, refer to the section ‘Guide for the Use and Application of the ASHRAE Data Center Classes’ and the detailed flowchart in Appendix F for the process needed to account for multiple server metrics that impact overall TCO. Equipment Environmental Specifications Product Operations (b)(c) Product Power Off (c) (d)
Classes (a)
Dry-Bulb Temperature (?C ) (e) (g) Humidity Range, non-Condensing (h) (i) Maximum Dew Point (?C) Maximum Elevation (m) Maximum Rate of Change(?C/hr) (f) Dry-Bulb Temperature (?C) Relative Humidity (%) Maximum Dew Point (?C)
Recommended (Applies to all A classes; individual data centers can choose to expand this range based upon the analysis described in this document) A1 5.5oC DP to to 18 to 27 60% RH and A4 15oC DP Allowable 20% to 80% A1 15 to 32 17 3050 5/20 5 to 45 8 to 80 27 RH 20% to 80% A2 10 to 35 21 3050 5/20 5 to 45 8 to 80 27 RH -12?C DP & 8% A3 5 to 40 24 3050 5/20 5 to 45 8 to 85 27 RH to 85% RH -12?C DP & 8% A4 5 to 45 24 3050 5/20 5 to 45 8 to 90 27 RH to 90% RH 8% RH to 80% B 5 to 35 28 3050 NA 5 to 45 8 to 80 29 RH 8% RH to 80% C 5 to 40 28 3050 NA 5 to 45 8 to 80 29 RH
a. b. c. Classes A1, A2, B and C are identical to 2008 classes 1, 2, 3 and 4. These classes have simply been renamed to avoid confusion with classes A1 thru A4. The recommended envelope is identical to that published in the 2008 version. Product equipment is powered on. Tape products require a stable and more restrictive environment (similar to Class A1). Typical requirements: minimum temperature is 15°C, maximum temperature is 32°C, minimum relative humidity is 20%, maximum relative humidity is 80%, maximum dew point is 22°C, rate of change of temperature is less than 5°C/h, rate of change of humidity is less than 5% RH per hour, and no condensation. Product equipment is removed from original shipping container and installed but not in use, e.g., during repair maintenance, or upgrade. A1 and A2 - Derate maximum allowable dry-bulb temperature 1°C/300 m above 950 m. A3 - Derate maximum allowable dry-bulb temperature 1°C/175 m above 950 m. A4 - Derate maximum allowable dry-bulb temperature 1°C/125 m above 950 m. 5°C/hr for data centers employing tape drives and 20°C/hr for data centers employing disk drives. With diskette in the drive, the minimum temperature is 10°C. o The minimum humidity level for class A3 and A4 is the higher (more moisture) of the -12 C dew point and the 8% relative o o humidity. These intersect at approximately 25 C. Below this intersection (~25C) the dew point (-12 C) represents the minimum moisture level, while above it relative humidity (8%) is the minimum. Moisture levels lower than 0.5?C DP, but not lower -10?C DP or 8% RH, can be accepted if appropriate control measures are implemented to limit the generation of static electricity on personnel and equipment in the data center. All personnel and mobile furnishings/equipment must be connected to ground via an appropriate static control system. The following items are considered the minimum requirements (see Appendix A for additional details): 1) Conductive Materials a) conductive flooring b) conductive footwear on all personnel that go into the datacenter, including visitors just passing through; c) all mobile furnishing/equipment will be made of conductive or static dissipative materials. 2) During maintenance on any hardware, a properly functioning wrist strap must be used by any personnel who contacts IT equipment.
d. e.
f. g. h.
i.
? 2011 American Society of Heating, Refrigerating and Air-Conditioning Engineers, Inc. All rights reserved.
8

The new guidelines were developed with a focus on providing as much information as possible to the data center operator to allow them to operate in the most energy efficient mode and still achieve the reliability necessary as required by their business. Two new data center classes are created to achieve the most flexibility in the operation of the data center. The four data center classes including the two new ones (A3 and A4) are shown in the psychrometric chart below.
A3
A4
A2 A1
Recommended Envelope
Figure 2. ASHRAE Environmental Classes for Data Centers ASHRAE Classes A3 and A4 have been added to expand the environmental envelopes for IT equipment. ASHRAE Classes A1, A2, B and C are identical to the 2008 version of Classes 1, 2, 3 and 4. Also, the 2008 recommended envelope stays the same. ASHRAE Class A3 expands the temperature range to 5 to 40oC while also expanding the moisture range from 8% RH and -12oC dew point to 85 % relative humidity. ASHRAE Class A4 expands the allowable temperature and moisture range even further than A3. The temperature range is expanded to 5 to 45oC while the moisture range extends from 8% RH and -12oC dew point to 90 % RH. Based on the allowable lower moisture limits for classes A3 and A4, there are some added minimum requirements that are listed in note i in the table. These pertain to the protection of the equipment from ESD failure-inducing events that could possibly occur in low moisture environments. ASHRAE TC 9.9 has a research project on the effects of ? 2011 American Society of Heating, Refrigerating and Air-Conditioning Engineers, Inc. All rights reserved. 9

low moisture environments on IT equipment. The research is intended to quantify the relationship between moisture content of the air and the severity of the impact of ESD events on functioning IT equipment. This project is scheduled over approximately the next two years and it may provide information that could relax some of these requirements as outlined in note i of the table and could allow a further relaxation of the lower limits on humidity. As shown in the above paragraphs and table, the maximum allowable limits have been relaxed to allow for greater flexibility in the design and operational states of a data center. One area that needed careful consideration was the application of the altitude derating. By simply providing the same derating curve as defined for Classes A1 and A2, the new A3 and A4 classes would have driven undesirable increases in server energy to support the higher altitudes upon users at all altitudes. In an effort to provide for both a relaxed operating environment, as well as a total focus on the best solution with the lowest TCO for the client, modification to this derating was applied. The new derating curves for Classes A3 and A4 maintain significant relaxation, while mitigating extra expense incurred both during acquisition of the IT equipment, but also under operation due to increased power consumption. See Appendix D for the derating curves. One may ask why the recommended envelope is now highlighted as a separate row in Table 4. There have been some misconceptions regarding the use of the recommended envelope. When it was first created, it was intended that within this envelope the most reliable, acceptable and reasonable power-efficient operation could be achieved. Data from the manufacturers were used to create the recommended envelope. It was never intended that the recommended envelope would be the absolute limits of inlet air temperature and humidity for IT equipment. As stated in the Thermal Guidelines book the recommended envelope defined the limits under which IT equipment would operate the most reliably while still achieving reasonably energy-efficient data center operation. However, as stated in the Thermal Guidelines book, in order to utilize economizers as much as possible to save energy during certain times of the year the inlet server conditions may fall outside the recommended envelope but still within the allowable envelope. The Thermal Guidelines book also states that it is acceptable to operate outside the recommended envelope for short periods of time without affecting the overall reliability and operation of the IT equipment. However, some still felt the recommended envelope was mandatory, even though that was never the intent. The impact of two key factors (reliability and power vs ambient temperature) that drove the previous inclusion of the recommended envelope is now provided as well as several other server metrics to aid in defining an envelope that more closely matches each user’s business and technical needs. The relationships between these factors and inlet temperature will now be provided thereby allowing data center operators to decide how they can optimally operate within the allowable envelopes.
? 2011 American Society of Heating, Refrigerating and Air-Conditioning Engineers, Inc. All rights reserved.
10

Guide for the Use and Application of the ASHRAE Data Center Classes
The addition of further data center classes significantly complicates the decision process for the data center owner/operator when trying to optimize efficiency, reduce total cost of ownership, address reliability issues, and increase performance. The table below attempts to capture many of the characteristics involved in the decision making process. The data center optimization is a complex multi-variate problem and requires a detailed engineering evaluation for any significant changes to be successful. Only following collection of the appropriate data and understanding the interactions within the data center should the evaluation of an alternative operating envelope be considered. Each parameter’s current and planned status could lead to a different endpoint for the data center optimization path. The worst case scenario would be for an end-user to assume that ITE capable of operating in class A3 or A4 would solve existing data center thermal management, power density or cooling problems due to their improved environmental capability. While the new IT equipment may operate in these classes, the data center problems will certainly be compounded thereby impacting data center energy use, cost, and reliability. The rigorous use of the tools and guidance in this whitepaper should preclude that. The following table summarizes the key characteristics and potential options to be considered when evaluating the optimal operating range for each data center. Table 5. Range of Options to Consider for Optimizing Energy Savings
Range of options New, retrofit, existing upgrade Layout and arrangement, economizer airflow path, Architectural aspects connections between old and new sections Extensive range, from none to full containment[1,2], room’s Airflow management performance against RCI and RTI metrics. Cooling controls sensor location Cooling system return, under floor, in-row, IT inlet Temperature/humidity rating of: power distribution equipment, cabling, switches and network gear, room Temperature/humidity rating of all instrumentation, humidification equipment, cooling unit existing equipment allowable supply and return temperatures, personnel health and safety requirements. Economizer None, to be added, existing, water-side, air-side Chiller None, existing Range of temperature in the region (obtain bin data and/or Climate Factors- Temperature design extremes), number of hours per year above potential ASHRAE class maximums Range of humidity in the region (obtain bin data and/or design extremes for RH and dewpoint), coincident temperature and Climate Factors - Humidity humidity extremes, number of hours per year outside potential ASHRAE class humidity ranges Cooling Architecture Air, liquid, perimeter, row, rack level 3 Data Center type HPC, internet, enterprise, financial Characteristic Project type
? 2011 American Society of Heating, Refrigerating and Air-Conditioning Engineers, Inc. All rights reserved.
11

1) 2) 3)
Some CRAC/CRAH units have limited return temperatures, as low as 30°C With good airflow management, server temperature rise can be on the order of 20°C, with an inlet of temperature of 40°C the hot aisle could be 60°C Data center type affects reliability/availability requirements
By understanding the characteristics described above along with the data center capability one can then follow the general steps necessary in setting the operating temperature and humidity range of the data center: Optimization Process: 1) Consider the state of best practices for the data center, implementation of most of these is a prerequisite before moving to a higher server inlet temperature operation, this includes airflow management as well as cooling system controls strategy 2) Determine maximum allowable ASHRAE class environment from 2011 ASHRAE Classes based on review of all IT equipment environmental specifications 3) Use the recommended operating envelope (See Table 4) or, if more energy savings is desired, use the following information to determine the operating envelope: a) Climate data for locale (only when utilizing economizers) b) Server Power Trend vs Ambient Temperature – see section A c) Acoustical Noise Levels in the Data Center vs Ambient Temperature – see section B d) Server Reliability Trend vs Ambient Temperature – see section C e) Server Reliability vs Moisture, Contamination and Other Temperature Effects – see section D f) Server Performance Trend vs Ambient Temperature – see section E g) Server Cost Trend vs Ambient Temperature – see section F The steps above provide a simplified view of the flowchart in Appendix F. The use of Appendix F is highly encouraged as a starting point for the evaluation of the options. The flowchart provides guidance to the data center operator on how to position their data center for operating in a specific environmental envelope. Possible endpoints range from optimization of TCO within the recommended envelope as specified in Table 4 to a chiller-less data center using any of the data center classes, but more importantly describes how to achieve even greater energy savings through the use of a TCO analysis utilizing the servers metrics provided in the next sections.
Server Metrics to Guide Use of New Guidelines
The development of the recommended envelopes for the 2004 and 2008 versions were based on the IT manufacturers’ knowledge of both the reliability and equipment power consumption trends of servers as a function of inlet air temperature. In order to use a different envelope providing greater flexibility in data center operation, some knowledge of these two factors must be provided. The next sections provide trend data for IT equipment for both power and reliability over a wide range of ambient temperatures. In addition, some aspects of server performance, acoustics, corrosion and cost vs. ambient temperature and humidity will also be discussed.
? 2011 American Society of Heating, Refrigerating and Air-Conditioning Engineers, Inc. All rights reserved.
12

A number of server metrics are presented in the sections below and are shown as ranges for the parameter of interest. The ranges are meant to capture most of the volume server market. If specific server information is desired, contact the IT manufacturer.
A. Server Power Trend vs Ambient Temperature
Data was collected from a number of IT equipment manufacturers covering a wide range of products. Most of the data collected for the A2 environment fell within the envelope displayed in Figure 3. The power increase is a result of both fan power, component power and the power conversion for each. The component power increase is a result of an increase in leakage current for some silicon devices. As an example of the usage of Figure 3, if a data center is normally operating at a server inlet temperature of 15oC and the operator wants to raise this temperature to 30oC, it could be expected that the server power would increase in the range of 4 to 8%. If the inlet temperature increases to 35oC, the IT equipment power could increase in the range of 7 to 20% compared to operating at 15oC. Since very few data center class products currently exist for the A3 class environment, the development of the A3 envelope shown in Figure 3 below was simply extrapolated from the A2 trend. (Note: Equipment designed for NEBS environments would likely meet the new class requirements but typically have limited features and performance in comparison with volume IT equipment). New products for this class would likely be developed with improved heat sinks and/or fans to properly cool the components within the new data center class, so the power increases over the wider range would be very similar to that shown for class A2.
1.25 1.25
Server Power Increase - x factor
Server Power Increase - x factor
1.20
1.20
1.15
1.15
1.10
1.10
1.05
1.05
1.00 10 15 20 25 30 35 40
1.00 10 15 20 25 30 35 40
Ambient Temperature - C
Ambient Temperature - C
A2
A3
Figure 3. Server Power Increase vs Ambient Temperature for Classes A2 and A3 With the increase in fan speed over the range of ambient temperatures IT equipment flowrate also increases. An estimate of the increase in server air flowrates over the temperature range of 10 to 35oC is displayed in the figure below.
? 2011 American Society of Heating, Refrigerating and Air-Conditioning Engineers, Inc. All rights reserved.
13

2.8 2.6
Server Air Flowrate Increase
2.4 2.2 2.0 1.8 1.6 1.4 1.2 1.0 10 15 20 25 30 35
Ambient Temperature - degrees C
Figure 4.Server Air Flowrate Increase vs Ambient Temperature Increase
B. Acoustical Noise Levels in the Data Center vs Ambient Temperature
Expanding the operating envelope for datacom facilities may have an adverse effect on acoustical noise levels. Noise levels in high-end datacenters have steadily increased over the years and have become, or at least will soon become, a serious concern to data center managers and owners. For background and discussion on this, see Chapter 9 “Acoustical Noise Emissions” in the ASHRAE datacom book entitled “Design Considerations for Datacom Equipment Centers.” The increase in noise levels is the obvious result of the significant increase in cooling requirements of new, high-end datacom equipment. The increase in concern results from noise levels in data centers approaching or exceeding regulatory workplace noise limits, such as those imposed by OSHA in the U.S. or by EC Directives in Europe. (See [3] for a good summary). Empirical fan laws generally predict that the sound power level of an air moving device increases with the 5th power of rotational speed, and this behavior has generally been validated over the years for typical high-end rack-mounted servers, storage units, and I/O equipment normally found on data center floors. This means that a 20% increase in speed (e.g., 3000 to 3600 rpm) equates to a 4 dB increase in noise level. The first phase of the new ASHRAE guidelines (2008 version) concerned raising the recommended operating temperature envelope by 2°C (from 25°C to 27°C). While it is not possible to predict a priori the effect on noise levels of a potential 2°C (3.6°F) increase in data center temperatures, it is not unreasonable to expect to see increases in the range of 3-5 dB. Data center managers and owners should therefore weigh the trade-offs between the potential benefits in energy efficiency with this original proposed new recommended operating environment and the potential risks associated with increased noise levels. With the new (2011) proposals to the ASHRAE guidelines described in this Whitepaper, concerning additional classes with widely extended operating temperature envelopes, it becomes instructive to look at the allowable upper temperature ranges and their potential effect on data center noise levels. Using the 5th power empirical law mentioned above, ? 2011 American Society of Heating, Refrigerating and Air-Conditioning Engineers, Inc. All rights reserved. 14

coupled with current practices for ramping-up air moving device speeds based on ambient temperature, the following A-weighted sound power level increases were predicted for typical air-cooled high-end server racks (containing typical mixes of power assemblies, CEC cages or drawers, I/O drawers, and modular water cooling units). Table 6. Expected Increase in A-Weighted Sound Power Level Expected Increase in A-Weighted Sound Power Level (in decibels) 25°C 30°C 35°C 40°C 45°C 0 dB 4.7 dB 6.4 dB 8.4 dB 12.9 dB Of course the actual increases in noise levels for any particular IT equipment rack depends not only on the specific configuration of the rack but also on the cooling schemes and fan speed algorithms used for the various rack drawers and components. However, the above increases in noise emission levels with ambient temperature can serve as a general guideline for data center managers and owners concerned about noise levels and noise exposure for employees and service personnel. The Information Technology Industry has developed its own internationally-standardized test codes for measuring the noise emission levels of its products, ISO 7779 [4], and for declaring these noise levels in a uniform fashion, ISO 9296 [5]. Noise emission limits for IT equipment installed in a variety of environments (including data centers) are stated in Statskontoret Technical Standard 26:6 [6]. The above discussion applies to potential increases in noise emission levels; that is, the sound energy actually emitted from the equipment, independent of listeners or the room or environment where the equipment is located. Ultimately, the real concern is about the possible increases in noise exposure, or noise immission levels, that employees or other personnel in the data center might be subject to. With regard to the regulatory workplace noise limits, and protection of employees against potential hearing damage, data center managers should check whether potential changes in the noise levels in their environment will cause them to trip various “action level” thresholds defined in the local, state, or national codes. The actual regulations should be consulted, because these are complex and beyond the scope of this document to explain fully. The noise levels of concern in workplaces are stated in terms of A-weighted sound pressure levels (as opposed to Aweighted sound power levels used above for rating the emission of noise sources). For instance, when noise levels in a workplace exceed a sound pressure level of 85 dB(A), hearing conservation programs are mandated, which can be quite costly, generally involving baseline audiometric testing, noise level monitoring or dosimetry, noise hazard signage, and education and training. When noise levels exceed 87 dB(A) (in Europe) or 90 dB(A) (in the US), further action such as mandatory hearing protection, rotation of employees, or engineering controls must be taken. Data center managers should consult with acoustical or industrial hygiene experts to determine whether a noise exposure problem will result when ambient temperatures are increased to the upper ends of the expanded ranges proposed in this Whitepaper. In an effort to provide some general guidance on the effects of the proposed higher ambient temperatures on noise exposure levels in data centers, the following observations ? 2011 American Society of Heating, Refrigerating and Air-Conditioning Engineers, Inc. All rights reserved. 15

can be made (but again, the caution is made to seek professional help in actual situations since regulatory and legal requirements are at issue). Modeling and predictions of typical IT equipment racks, with typical front-rear directivity, in typical data centers have shown that the sound pressure level in the center of a typical aisle between two rows of continuous racks will reach the regulatory trip level of 85 dB(A) when each of the individual racks in the rows has a measured (as opposed to a statistical upper limit) sound power levels of roughly 8.4 B (84 dB sound power level). If it is assumed that this is the starting condition for a 25°C ambient data center temperature—and many typical highend server racks today are at or above this 8.4-B level—the sound pressure level in the center of the aisle would be expected to increase to 89.7 dB(A) at 30°C ambient, to 91.4 dB(A) at 35°C ambient, to 93.4 dB(A) at 35°C ambient, and to 97.9 dB(A) at 45°C ambient, using the predicted increases to sound power level above. Needless to say, these levels are extremely high. They are not only above the regulatory trip levels for mandated action (or fines, in the absence of action), but they clearly pose a risk of hearing damage unless controls are instituted to avoid exposure by data center personnel.
C. Server Reliability Trend vs Ambient Temperature
Before embarking on the path of extensive use of data center economizers or wider environmental operating limits, it is important to understand the reliability (failure rate) impact of those changes. The hardware failure rate within a given data center will be determined by the local climate, the type of economization being implemented, and the temperature and humidity range over which economization is being carried out. Most economized facilities have a means of mixing hot exhaust air with incoming cold air so the minimum data center temperature is usually tempered to something in the range of 15 to 20oC. All of the IT equipment (servers, storage, networking, power, etc.) in a data center using an economizer must be rated to operate over the planned data center class of temperature and humidity range. To understand the impact of temperature on hardware failure rates one can model different economization scenarios. First, consider the ways economization can be implemented and how this would impact the data center temperature. For purposes of this discussion, consider three broad categories of economized facilities: 1) Economization over a narrow temperature range with little or no change to the data center temperature. This is the primary control methodology, where the data center is properly configured controlling the air temperature at or near the IT inlet to the data center operators chosen temperature. The economizer modulates to bring in more or less cool air (air-side) or adjust the cool water flow or temperature (water-side) to meet this required temperature. If the external conditions or internal load change such that the economizer can no longer handle the task on its own, the chiller will ramp up providing additional cooling capacity thereby keeping the space at the desired temperature. This is the most benign implementation of economizing so the temperature of the data center is essentially the same as if the data center was not economized. If there is little or no temperature change then there should be little or no failure rate impact of ? 2011 American Society of Heating, Refrigerating and Air-Conditioning Engineers, Inc. All rights reserved. 16

temperature on the data center hardware from temperature. This economization scenario probably represents the vast majority of economized data centers. 2) Expanded temperature range economization where there may be a net increase in the data center temperature some of the time. Some data centers may choose to take advantage of more hours of economization by raising their data center temperature limits and widening the temperature range over which they will operate their facility. 3) A chiller-less data center facility where the data center temperature is higher and varies with the outdoor air temperature and local climate. Some data centers in cool climates may want to reduce their data center construction capital costs by building a chiller-less facility. In chiller-less data center facilities, the temperature in the data center will vary over a much wider range that is determined, at least in part, by the temperature of the outdoor air and the local climate. These facilities may use supplemental cooling methods that are not chiller-based such as evaporative cooling. In the following section the impact of expanded temperature and chiller-less economization on hardware failure rates is analyzed. The discussion that follows is not meant to imply a specific data center environmental control algorithm. The method and approach was chosen to facilitate analysis of the data in a simple manner that illustrates key findings. To understand the impact of the use of a chiller-less economized data center implementation on hardware failure rates, consider the city of Chicago as an example. When the time-at-temperature climate data for Chicago is plotted as a histogram as shown in Figure 5, one can see the vast majority of the hours in a year are spent at cool and cold temperature (below 20oC) and, while Chicago does get hot in the summer, those hot periods do not last long and comprise only a very small percentage of the hours in a given year.
? 2011 American Society of Heating, Refrigerating and Air-Conditioning Engineers, Inc. All rights reserved.
17

1600 1400 1200
Hours During Year 2010
1000 800 600 400 200 0
-10 to -5 -20 to -15 -15 to -10 5 to 10 10 to 15 -5 to 0 0 to 5 15 to 20C 20 to 25C 25 to 30C
30 to 35C
Dry Bulb Temperature ( C)
Figure 5. Histogram of dry bulb temperatures for the city of Chicago for the year 2010. With an air-side economizer the data center fans will do some work on the incoming air and will raise its temperature by about 1.5oC going from outside the data center to the inlet of the IT equipment. Also, most data centers with economizers have a means of air mixing to maintain a minimum data center temperature in the range of 15 to 20oC, even in the winter. Applying these assumptions to the Chicago climate data, the histogram transforms into the one shown in Figure 6.
7000
6000
Hours During Year 2010
5000
4000
3000
2000
1000
0
15 to 20C
20 to 25C
Dry Bulb Temperature ( C)
Figure 6. 2010 dry bulb temperatures for Chicago with economization assumptions applied. Assumptions include reuse of server exhaust heat to maintain a minimum 15 to 20oC temperature and a 1.5oC temperature rise from outdoor air to server inlet. ? 2011 American Society of Heating, Refrigerating and Air-Conditioning Engineers, Inc. All rights reserved. 18
25 to 30C
30 to 35C

Taking the histogram data in Figure 6, and calculating a percentage of time spent in each temperature band, one can create a simple time-at-temperature weighted average of the equipment failure rate as shown in Table 6. Table 7. Time-at-temperature weighted failure rate calculation for IT equipment in the city of Chicago.
Location Chicago, IL 15 -20C % of Hours 67.6% 15 -20C x-factor 0.865 20 - 25C % of Hours 17.2% 20 - 25C x-factor 1.13 25 - 30C % of Hours 10.6% 25 - 30C x-factor 1.335 30 - 35C % of Hours 4.6% 30 - 35C x-factor 1.482 Net x-factor 0.99
The values in the columns marked “x-factor” are the relative failure rate for that temperature bin. As temperature increases, the equipment failure rate will also increase. A table of equipment failure rate as a function of continuous (7 days x 24 hours x 365 days per year) operation is given in Appendix C for volume servers. For an air-side economizer, the net time-weighted average reliability for a data center in Chicago is 0.99 which is very close to the value of 1 for a data center that is tightly controlled and continuously run at a temperature of 20oC. Even though the failure rate of the hardware increases with temperature, the data center spends so much time at cool temperatures in the range of 15 to 20oC (where the failure rate is slightly below that for 20oC continuous operation) that the net reliability of the IT equipment in the datacenter over a year is very comparable to the ITE in a datacenter that is run continuously at 20oC. One should note that, in a data center with an economizer, the hardware failure rate will tend to be slightly higher during warm periods of the summer and slightly lower during cool winter months and about average during fall and spring. In general, in order to make a data center failure rate projection one needs an accurate histogram of the time-at-temperature for the given locale, and one should factor in the appropriate air temperature rise from the type of economizer being used as well as the data center environmental control algorithm. For simplicity, the impact of economization on the reliability of data center hardware has been analyzed with two key assumptions: a) a minimum data center temperature of 15 to 20°C can be maintained, and b) the data center temperature tracks with the outdoor temperature with the addition of a temperature rise that is appropriate to the type of economization being used. However, the method of data analysis in this paper is not meant to imply or recommend a specific algorithm for data center environmental control. A detailed treatise on economizer approach temperatures is beyond the scope of this paper. The intent is to demonstrate the methodology applied and provide general guidance. An engineer well versed in economizer designs should be consulted for exact temperature rises for a specific economizer type in a specific geographic location. A reasonable assumption for data center supply air temperature rise above the outdoor ambient dry bulb (DB) temperature is assumed to be 1.5oC for an air-side economizer. For water-side economizers the temperature of the cooling water loop is primarily dependent on the wet bulb (WB) temperature of the outdoor air. Again, using Chicago as an example, data from the ASHRAE Weather Data Viewer [7] shows that the mean dry bulb temperature coincident ? 2011 American Society of Heating, Refrigerating and Air-Conditioning Engineers, Inc. All rights reserved. 19

with wet bulb temperature shows roughly a 5oC rise. (e.g. When the WB is 20oC the mean DB temperature coincident with the 20oC WB is 25oC DB.). If one assumes that the tower and heat exchangers have a reasonably close approach temperature, then on the average day in Chicago the water-side economizer should also be able to provide data center supply air 1.5oC above the outdoor dry bulb. For water-side economization with a dry-cooler type tower (closed loop, no evaporation) a 12oC air temperature rise of the data center air above the outdoor ambient air temperature is assumed. It is worth reiterating that the following data sets were based upon the above assumptions and that different geographies (with different WB/DB combinations) will have different temperature rise based on the specifics of the economizer in place. That stated, the differences between the 1.5oC rise and the 12oC rise for the same cities indicate that if they are a degree or two off that the result will be well within the error bars. Time-at-temperature weighted average failure rate projections are shown below in Figures 7, 8, 9 and 10 for selected US and world-wide cities for different economizer scenarios. The calculations for those graphs, including the percentage of hours spent within each temperature range for each city, and the reliability data as a function of temperature can be found in Appendix C. It is important to be clear what the relative failure rate values mean. We have normalized the results to a data center run continuously at 20°C; this has the relative failure rate of 1.0. For those cities with values below 1.0, the implication is that the economizer still functions and the data center is cooled below 20°C (to 15°C) for those hours each year. In addition the relative failure rate shows the expected increase in the number of failed servers, not the percentage of total servers failing; e.g. if a data center that experiences 4 failures per 1000 servers incorporates warmer temperatures and the relative failure rate is 1.2, then the expected failure rate would be 5 failures per 1000 servers. To provide a further frame of reference on data center hardware failures references [4,5] showed blade hardware server failures were in the range of 2.5 to 3.8% over twelve months in two different data centers with supply temperatures of approximately 20oC. In a similar data center that included an air-side economizer with temperatures occasionally ranging to 35oC (at an elevation around 1600m) the failure rate was 4.5%. These values are provided solely to provide some guidance with an example of failure rates. Failure in that study was defined as anytime a server required hardware attention. No attempt to categorize the failure mechanisms was made.
? 2011 American Society of Heating, Refrigerating and Air-Conditioning Engineers, Inc. All rights reserved.
20

化工原理传热综合实验报告数据处理七、实验数据处理 1.蒸汽冷凝与冷空气之间总传热系数K 的测定，并比较冷空气以不同流速u 流过圆形直管时，总传热系数K 的变化。实验时蒸汽压力：0.04MPa （表压力），查表得蒸汽温度T=109.4℃。实验装置所用紫铜管的规格162mm mm φ?、 1.2l m =，求得紫铜管的外表面积 200.010.060318576281.o S d l m m m ππ=??=??=。根据2 4s s V V u A d π= =、0.012d m =，得到流速u ，见下表2：表2 流速数据取冷空气进、出口温度的算术平均值作为冷空气的平均温度，查得冷空气在不同温度下的比热容p c 、黏度μ、热传导系数λ、密度ρ，如下表3所示：表3 查得的数据 t 进/℃ t 出/℃ t 平均/℃ ()p c J kg ????? ℃ Pa s μ? ()W m λ?????℃ ()3 kg m ρ-? 22.1 77.3 49.7 1005 0.0000196 0.0283 1.093 24.3 80.9 52.6 1005 0.0000197 0.02851 1.0831 26.3 82.7 54.5 1005 0.0000198 0.02865 1.0765 27.8 83 55.4 1005 0.0000198 0.02872 1.0765 29.9 83.6 56.75 1005 0.0000199 0.02879 1.0699 31.8 83.7 57.75 1005 0.00002 0.02886 1.0666 33.7 83.8 58.75 1005 0.0000200 0.02893 1.0633 35.6 84 59.8 1005 0.0000201 0.029 1.06 根据公式()()=V s p s p Q m c t t c t t ρ=--出进出进、 ()()ln m T t T t t T t T t ---?=--进出进出，求出Q 序号 ()31s V m h -? ()1u m s -? 1 2.5 6.140237107 2 5 12.28047421 3 7.5 18.42071132 4 10 24.56094843 5 12.5 30.70118553 6 15 36.84142264 7 17.5 42.98165975 8 20 49.12189685

化学实验教学中心实验报告化学测量与计算实验Ⅱ 实验名称：气-汽对流传热综合实验报告学生姓名：学号：院（系）：年级：级班指导教师：研究生助教：实验日期： 2017.05.26 交报告日期： 2017.06.02

（二）强化管换热器传热系数、准数关联式及强化比的测定强化传热又被学术界称为第二代传热技术，它能减小初设计的传热面积，以减小换热器的体积和重量；提高现有换热器的换热能力；使换热器能在较低温差下工作；并且能够减少换热器的阻力以减少换热器的动力消耗，更有效地利用能源和资金。强化传热的方法有多种，本实验装置是采用在换热器内管插入螺旋线圈的方法来强化传热的。螺旋线圈的结构图如图1所示，螺旋线圈由直径 3mm以下的铜丝和钢丝按一定节距绕成。将金属螺旋线圈插入并固定在管内，即可构成一种强化传热管。在近壁区域，流体一面由于螺旋线圈的作用而发生旋转，一面还周期性地受到线圈的螺旋金属丝的扰动，因而可以使传热强化。由于绕制线圈的金属丝直径很细，流体旋流强度也较弱，所以阻力较小，有利于节省能源。螺旋线圈是以线圈节距H与管内径d的比值技术参数，且长径比是影响传热效果和阻力系数的重要因素。科学家通过实验研究总结了形式为αα=Bααα的经验公式，其中B和m的值因螺旋丝尺寸不同而不同。采用和光滑套管同样的实验方法确定不同流量下得Rei和αα，用线性回归方法可确定B和m的值。单纯研究强化手段的强化效果（不考虑阻力的影响），可以用强化比的概念作为评 ?，其中αα是强化管的努塞尔准数，αα0是普通管判准则，它的形式是：αααα0 ?>1，而且它的值越大，强化效果越好。的努塞尔准数，显然，强化比αααα0

导语：主要分析本月毛利率、毛利额情况，与去年同期对比情况,以下为大家介绍淘宝数据分析报告模板文章，欢迎大家阅读参考!淘宝数据分析，实际是电商数据分析，归结到底还是零售数据分析，给你一些分析的思路，权当做抛砖引玉。总体来说可以分为商品分析、客户分析、地区分析、时间分析四大维度（参考数据雷达的分析思路）。在这里我重点说商品分析。 1、销售状况分析：主要分析本月销售情况、本月销售指标完成情况、与去年（或上月）同期对比情况。通过这组数据的分析可以知道同比销售趋势、实际销售与计划的差距。 2、销售毛利分析：主要分析本月毛利率、毛利额情况，与去年同期对比情况。通过这组数据的分析可以知道同比毛利状况，以及是否在商品毛利方面存在不足。 3、营运可控费用分析：主要是本月各项费用明细分析、与去年同期对比情况，有无节约控制成本费用。这里的各项费用是指：员工成本、能耗、物料及办公用品费用、维修费用、存货损耗、日常营运费用（包括电话费、交通费、垃圾费等），通过这组数据的分析可以清楚的知道门店营运可控费用的列支，是否有同比异常的费用发生、有无可以节约的费用空间。 4、橱窗效率：主要是本月橱窗效率情况、与去年同期对比。“日均橱窗效率”是指“日均每个橱窗平均销售额”，即：日均橱窗商品销售金额/橱窗个数。 5、人均劳效（人效）：主要是本月人均劳效情况、与去年同期对比。“本月人均劳效”计算方法：本月销售金额/本月总营业人数。 6、盘点损耗率分析：主要是门店盘点结果简要分析，通过分析及时发现商品进、销、存各个环节存在的问题。该指标指标仅对大店或销量日均100以上店铺适用。 7、库存分析：主要是本月平均商品库存、库存结构、库龄情况、周转天数，与去年同期对比分析。通过该组数据的分析可以看出库存是否出现异常，

传热膜系数测定实验（第四组）一、实验目的 1、了解套管换热器的结构和壁温的测量方法 2、了解影响给热系数的因素和强化传热的途径 3、体会计算机采集与控制软件对提高实验效率的作用 4、学会给热系数的实验测定和数据处理方法二、实验内容 1、测定空气在圆管内作强制湍流时的给热系数α1 2、测定加入静态混合器后空气的强制湍流给热系数α1’ 3、回归α1和α1’联式4.0Pr Re ??=a A Nu 中的参数A 、a * 4、测定两个条件下铜管内空气的能量损失二、实验原理间壁式传热过程是由热流体对固体壁面的对流传热，固体壁面的热传导和固体壁面对冷流体的对流传热三个传热过程所组成。由于过程复杂，影响因素多，机理不清楚，所以采用量纲分析法来确定给热系数。 1）寻找影响因素物性：ρ，μ ，λ，c p 设备特征尺寸：l 操作：u ，βg ΔT 则：α=f （ρ，μ，λ，c p ，l ，u ，βg ΔT ） 2）量纲分析 ρ[ML -3]，μ[ML -1 T -1]，λ[ML T -3 Q -1]，c p [L 2 T -2 Q -1]，l [L] ，u [LT -1]， βg ΔT [L T -2]， α[MT -3 Q -1]] 3）选基本变量（独立，含M ，L ，T ，Q-热力学温度） ρ，l ，μ, λ 4）无量纲化非基本变量 α：Nu ＝αl/λ u: Re ＝ρlu/μ c p : Pr ＝c p μ/λ βg ΔT : Gr ＝βg ΔT l 3ρ2/μ2 5）原函数无量纲化 6）实验 Nu ＝ARe a Pr b Gr c 强制对流圆管内表面加热：Nu ＝ARe a Pr 0.4 圆管传热基本方程：热量衡算方程：圆管传热牛顿冷却定律：圆筒壁传导热流量：)]/()ln[)()()/ln(11221122121 2w w w w w w w w t T t T t T t T A A A A Q -----?-?=δλ 空气流量由孔板流量测量：54.02.26P q v ??= [m 3h -1，kPa] 空气的定性温度：t=(t 1+t 2)/2 [℃]

淘宝后台数据分析数据的价值有多少人来过我的店铺？什么时间来？从哪里来？这些数据是我们每天必需掌握的数据，店里的哪些商品会比较热卖，我们所做的运营和决策都必需依赖大量准确地数据，很多部门需要这些数据，包括产品设计部门、营销推广部门、运营管理部门、售后服务部门没有数据就没有发言权，任何的决策、管理都必须以数据为支撑数据采集 1.店铺运营的基础数据流量数据：页面停留时间、访问深度、访客数等销售数据：成交用户数、客单价、支付宝成交量率等转化数据：UV转化率、宝贝页面成交转化率、Call in转化率、询单转化率等，以下为我们要重点分析的数据：流量数据浏览量（ＰＶ）/访客数（ＵＶ）=平均访问深度也就是说每个人平均的访问页面，这里我们希望数值越高越好，这样代表我们店铺的产品具有一定的黏度，客户停留时间长，这样买家才有可能令买家产生购买的冲动，我们的客服才有时间去进行引导销售还有同样要关注的是宝贝页浏览量、宝贝页访客数。销售数据在量子里面有一个销售分析模块，看到拍下的总金额和支付宝成交金额和客单价，用支付宝成交金额/拍下的总金额=支付宝成交率

这个支付宝成交率在参加活动和运营考核上都是非常重要的，原因当我们支付宝使用率高的时候我们买家她在拍下你的产品之后她是非常愿意去付款的，不会因其他原因拍下了不愿付款而流失掉，这样表示我们的产品对顾客有足够吸引力的，也可以反映我们的销售团队能否有足够的能力让顾客来购买产品，同时，我们换一个角度在拍下没有付款的客户，我们去催款，形成交易，这样催款成交，远远比我们去开发一个新客户容易的多，所以我们要留意这些数据，不要忽略了这种催款的成交。 Call in转化率=咨询用户数/访客数询单转化率=成交用户数/咨询用户数数据分析就是总结规律找原因数据公式：销售额=UV*UV转化率*客单价销售额=宝贝页访客数*宝贝页成交转化率*客单价这些公式可以为我们带来提示，访客数也就是我们的流量流量=推广+搜索+其他推广流量来自于硬广、钻石展位、直通车。淘宝客、专题活动搜索流量来自于名称搜索、类目搜索其他流量来自于收藏及后台、江湖及帮派、直接访问、站外推广、其他如果我们销售额没有达到预期，我们来分析是流量原因，还是转化率原因，还是客单价的原因，如果是流量原因，那么我们的推

深对其概念和影响因素的理解，并应用线性回归分析方法，确定关联式 Nu = A * Re * Pr 实验研究，测定其准数关联式 Nu = B * Re 中常数 B 、m 的值和强化比 Nu / Nu 0 ，了解强化 ② 对α i 的实验数据进行线性回归，求关联式 Nu=ARe Pr 中常数 A 、m 的值。 ② 对α i 的实验数据进行线性回归，求关联式 Nu=BRe 中常数 B 、m 的值。气—气传热综合实验讲义一、实验目的： 1．通过对空气—水蒸气简单套管换热器的实验研究，掌握对流传热系数 α i 的测定方法，加 m 0.4 中常数 A 、m 的值； 2．通过对管程内部插有螺旋线圈和采用螺旋扁管为内管的空气—水蒸气强化套管换热器的 m 传热的基本理论和基本方式； 3．了解套管换热器的管内压降 ?p 和 Nu 之间的关系；二、实验内容：实验一： ① 测定 5~6 个不同流速下简单套管换热器的对流传热系数α i 。 m 0.4 ③ 测定 5~6 个不同流速下简单套管换热器的管内压降 ?p 1。实验二： ① 测定 5~6 个不同流速下强化套管换热器的对流传热系数α i 。 m ③ 测定 5~6 个不同流速下强化套管换热器的管内压降 ?p 2 。并在同一坐标系下绘制普通管 ?p 1 ~Nu 与强化管 ?p 2 ~Nu 的关系曲线。比较实验结果。 ④ 同一流量下，按实验一所得准数关联式求得 Nu 0，计算传热强化比 Nu/Nu 0。三、实验原理实验一普通套管换热器传热系数及其准数关联式的测定 1. 对流传热系数α i 的测定对流传热系数α i 可以根据牛顿冷却定律，用实验来测定。

本科实验报告（阅）实验名称:非良导体热导率的测量实验11 非良导体热导率的测量【实验目的和要求】 1.学习热学实验的基本知识和技能。 2.学习测量非良导体热导率的基本原理的方法。 3.通过做物体冷却曲线和求平衡温度下物体的冷却速度，加深对数据图事法的理解。【实验原理】热可以从温度高的物体传到温度低的物体，或者从物体的高温部分传到低温部分，这种现象叫做热传递。热传递的方式有三种：传导，对流和辐射。设有一厚度为l、底面积为S?的薄圆板，上下两底面的温度T ，T 不相等，且T1＞T2，则有热量自上底面传乡下底面（见图1），其热量可以表示为 (1)

图1 测量样品式中，为热流量，代表单位时间里流过薄圆板的热量；为薄圆板内热流方向上的温度梯度，式中的负号表示热流方向与温度梯度的方向相反；为待测薄圆板的热导率。如果能保持上下两底面的温度不变（稳恒态）和传热面均匀，则，于是 (2) 得到关键1.使待测薄圆板中的热传导过程保持为稳恒态。 2.测出稳恒态时的。 1．建立稳恒态为了实现稳恒态，在试验中将待测薄圆板B置于两个直径与B相同的铝圆柱A,C 之间，且紧密接触，（见图2）。图二测量装置 C内有加热用的电阻丝和用作温度传感器的热敏电阻，前者被用来做热源。首先，

可由EH-3数字化热学实验仪将C内的电阻丝加热，并将其温度稳定在设定的数值上。B的热导率尽管很小，但并不为零，固有热量通过B传递给A，使A的温度T A逐渐升高。当T A高于周围空气的温度时，A将向四周空气中散发热量。由于C的温度恒定，随着A的温度升高，一方面通过C通过B流向A的热流速率不断减小，另一方面A向周围空气中散热的速率则不断增加。当单位时间内A 从B 获得的热量等于它向周围空气中散发的热量时，A的温度就稳定不变了。 2.测量稳恒态时的因为流过B的热流速率就是A从B获的热量的速率，而稳恒态时流入A的热流速率与它散发的热流速率相等，所以，可以通过测A在稳恒态时散热的热流速率来测。当A单独存在时，它在稳恒温度下向周围空气中散热的速率为（3）式中，为A的比热容；为A的质量；n=T=T2成为在稳恒温度T2时的冷却速度。 A的冷却速度可通过做冷却曲线的方法求得。具体测法是：当A、C已达稳恒态后，记下他们各自的稳恒温度T2,T1后，再断电并将B移开。使A，C接触数秒钟，将A 的温度上升到比T2高至某一个温度，再移开C，任A自然冷却，当TA降到比T2约高To（℃）时开始计时读数。以后每隔一分钟测一次TA,直到TA 低于T2约To（℃）时止。测的数据后，以时间t为横坐标，以TA为纵坐标做A 的冷却曲线，过曲线上纵坐标为T2的点做此曲线的切线，则斜率就是A在TA 的自然冷却速度，即（4）于是有（5）但要注意，A自然冷却时所测出的与试验中稳恒态时A散热是的热流速率是不同的。因为A在自然冷却时，它的所有外表面都暴漏在空气中，都可以散热，而在实验中的稳恒态时，A的上表面是与B接触的，故上表面是不散热的。由传热定律：物体因空气对流而散热的热流速率与物体暴露空气中的表面积成正比。设A的上下底面直径为d，高为h，则有（6）

淘宝运营考试试卷一、判断题 1．QQ群也可以进行二次营销。（A） A．正确 B. 错误 2.前后交叉布光使商品顶部受光，正面没有完全受光，适合拍摄外形扁平的小商品，不适合拍摄立体感较强且有一定高度的产品。（A） A．正确 B. 错误 3.催情咖啡在淘宝上是允许出售的。（B） A．正确 B. 错误 4.当我们查看店铺的每日流量图时，橙色的线条代表的是访客数，而兰色的线条代表的是浏览量。（B） A. 正确 B. 错误 5. 小李认为，只要每天的UV足够多，店铺就一定能发展的很好（B） A. 正确 B. 错误 6.聚划算的宝贝必须要入仓（B） A. 正确 B. 错误 7.店铺危机中可怕的是顾客死缠烂打，不依不饶（B） A. 正确 B. 错误 8.动态评分会影响商品在淘宝搜索中的排名顺序（A） A. 正确 B. 错误 9.直接转化是有效的下单行为，而间接转化不是有效的下单行为（B） A. 正确 B. 错误 10.微信不是二次营销工具（B） A. 正确 B. 错误 11.运营在网店工作中需要做到对网店流量监控分析、目标用户行为研究、网店日常更新及内容编辑、网络营销策划推广这些工作（A） A. 正确 B. 错误 12.店铺基础页可以做成文字型介绍页面，也可以做成商品促销型页面（A） A. 正确 B. 错误 13.活动能给我们带来的好处是：薄利多销、清库存、打爆款、引流（A） A. 正确 B. 错误

14.直通车推广是烧钱的，花费越多越好（B） A. 正确 15.钻石展位是靠展现来扣费的（A） A. 正确 B. 错误 16.停留时间的含义是：用户打开本店最后一个页面的时间减去打开本店第一个页面的时间点（A） A. 正确 B. 错误 17.申请天天特价需要店铺等级3钻以上才可以（B） A. 正确 B. 错误 18、一般来讲一个优质的宝贝标题包含促销词、属性名词和热搜关键词。（A） A. 正确 B. 错误 19、关联营销的主要目的是为了提升客单价（A） A. 正确 B. 错误 20、企业通过微博开展宣传推广都是为了带来更多的销售（A） A. 正确 B. 错误 21、通过论坛推广可以直接发店铺的产品信息（B） A. 正确 B. 错误 22、蘑菇街和美丽说都是属于购物类社会化媒体平台（A） A. 正确 B. 错误 23、衡量卖家通过网络投放广告的终极效果指标是带来的UV。（B） A. 正确 B. 错误 24、对于一家业务一般的中小卖家，付费广告是唯一能提升和改变的手段（B） A. 正确 B. 错误 25、一个卖家,自己工厂生产的产品,由于知道淘宝流量很大，人气很旺，他们在淘宝上发布的产品，注明“5件起批”，这样是可以的，客户很明确他们的最小起订量。（B） A. 正确 B. 错误 26、商品在接近下架的时候是流量最低的时候,所以这时候需要抓紧时间上架新的产品（B） A. 正确 B. 错误 27、为了避免分散买家的注意力,宝贝详情页中,最好不要显示关联销售的产品（B） A. 正确 B. 错误

淘宝运营测试题姓名：一、情景题 1、A店最近销售额下降，老板委派运营小李进行店铺数据分析，那么小李如何做呢？（1）.首先确定影响销售额的数据指标有哪几个？（） A.转化率 B.客单价 C.UV D.投资回报率（2）其次从哪个数据工具可以获得影响销售额的数据指标所对应的数据（） A.生E经 B.量子恒道 C.淘宝指数 D.客服软件（3）做了数据整理后，发现免费流量来源比重减少，下面哪些是属于免费流量来源呢？（） A.淘宝自然搜索 B.直通车 C.直接访问 D.淘宝客（4）店铺首页有多新品，小李想把最受用户喜欢的新品宝贝放在最醒目的位置，通过热力装修图能判断哪个宝贝最受欢迎（） A.正确 B.错误（5）这些新产品的点击转化并不是很理想，想把店内近期热销款换到第一屏，通过淘宝指数就能实现。（） A.正确 B.错误 2、张老板想请一个运营，但不知道应该让运营做那些工作，张老板希望让运营给店铺运营好，增加客户体验度。（1）一个标准的运营需要具备哪些条件？（） A.丰富的知识储备 B.用数据说话的能力

C.长远发展的眼光 D.良好的沟通协调能力（2）运营日常都应该做哪些工作？（） A.产品更新 B.店铺日常维护 C.编写宝贝标题 D.编写宝贝细节描述（3）运营可以通过对顾客能力的挖掘从而获得客户需求。（） A.正确 B.错误（4）客户体验可以通过哪些方面提升？（） A.服务 B.专业度 C.人性化 D.性格（5）客户应该从哪些维度来锁定（） A.性格 B.收入 C.年龄 D.职业 3、王翔是一家网店的店主，目前已经做到5颗心。冲钻是他现阶段的主要任务。他店铺经营的产品主要是日用品，比如牙刷、牙膏、洗发水、沐浴露等。由于店铺规模不算很大，他自己既是老板也是客服。 (1).【单选题】在他店里售卖的所有沐浴露中，力士的沐浴露他在进货渠道上最有优势，因此他把力士沐浴露定为店铺的促销品。促销品最主要的作用为？（） A.帮助店铺带来流量 B.帮助店铺带来利润 C.帮助店铺提升形象 (2).【判断题】在他店铺的所有商品中牙刷是属于价格比较低的，因此可以作为秒杀品，帮助他店铺冲钻。（） A.正确 B.错误

7.4 传热综合实验(20170424版本) 7.4.1实验目的与要求 1.通过实验，加深对传热理论的理解，提高研究和解决传热实际问题的能力； 2.通过对空气—水蒸气简单套管换热器的实验研究，掌握对流传热系数i α的测定方法，加深对其概念和影响因素的理解。 3.通过对管程内部插有螺旋线圈的空气—水蒸气强化套管换热器的实验研究，掌握对流传热系数i α的测定方法，加深对其概念和影响因素的理解。 4.学会并应用线性回归分析方法，确定传热管关联式4 .0Pr Re m A Nu =中的常数A 和m 的数值，强化管关联式4.00Pr Re m B Nu =中B 和m 数值。 5.根据计算出的Nu 、Nu 0求出强化比Nu/Nu 0，比较强化传热的效果，加深理解强化传热的基本理论和方式。 6.通过变换列管换热器换热面积实验测取数据计算总传热系数K ，加深对其概念和影响因素的理解。 7.认识套管换热器（光滑、强化）、列管换热器的结构及操作方法，测定并比较不同换热器的性能。 7.4.2实验原理在工业生产中，间壁换热是经常使用的换热方式。热流体借助于传热壁面，将热量传递给冷热体，以满足生产工艺的要求。影响换热器传热速率的参数有传热面积、平均温度差和传热系数三要素。为了合理选用或设计换热器，应对其性能有充分的了解。除了查阅文献外，换热器性能实测是重要的途径之一。传热系数是度量换热器性能的重要指标。为了提高能量的利用率，提高换热器的传热系数以强化传热过程，在生产实践中是经常遇到的问题。冷热液体间的传热过程是由热流体对壁面的对流传热、间壁的热传导、以及壁面对冷流体的对流传热这三个传热子过程组成。如7.4-1所示。在忽略了换热管内外两侧的污垢热阻后，以冷流体一侧传热面积为基准的传热系数计算式为： o o i m i i A A A A K αλδα+ += 11 (7.4-1) 式中：K ——以冷流体一侧传热面积为基准的总传热系数，)/(2℃?m W ；图7.4-1 间壁式传热过程示意图

实验四传热实验、实验目的 (1) 了解间壁式传热元件，掌握给热系数测定的实验方法。 (2) 学会给热系数测定的实验数据处理方法。 (3) 观察水蒸气在水平管外壁上的冷凝现象。 (4) 掌握热电阻测温的方法。 (5) 了解影响给热系数的因素和强化传热的途径二、实验原理在工业生产过程中，大量情况下，冷、热流体系通过固体壁面(传热元件)进行热量交换，称为间壁式换热。如图(4 - 1)所示，间壁式传热过程由热流体对固体壁面的对流传热, 固体壁面的热传导和固体壁面对冷流体的对流传热所组成。图4-1间壁式传加程示意图达到传热稳定时，有 Q -—爲)=卿/■沖仏一人.) -%4(丁-為)輛-场血(斥-咖式中：Q —传热量，J / s ; m —热流体的质量流率，kg / s C PI—热流体的比热，J / (kg ? C)； T i —热流体的进口温度，C； T2 —热流体的出口温度，C； m —冷流体的质量流率，kg / s (4-1 ) T

C p2 —冷流体的比热，J /（kg ? C ）； 11 —冷流体的进口温度，C； t2 —冷流体的出口温度，C； 2 :-1 —热流体与固体壁面的对流传热系数，W / （m C ）; A—热流体侧的对流传热面积，m； "；| —热流体与固体壁面的对数平均温差，C； 2 :-2 —冷流体与固体壁面的对流传热系数，W / （m C ）；A—冷流体侧的对流传热面积，m； |f\ —固体壁面与冷流体的对数平均温差，C； K —以传热面积A为基准的总给热系数，W / （m 2C）； —冷热流体的对数平均温差，C；热流体与固体壁面的对数平均温差可由式（4—2）计算, —［「J （4 - 2）亠4 一5 式中：T1 —热流体进口处热流体侧的壁面温度，C； TA2 —热流体出口处热流体侧的壁面温度，C。固体壁面与冷流体的对数平均温差可由式（4—3）计算, r - ：（4 —3） In切7 式中：t wi —冷流体进口处冷流体侧的壁面温度，C； t W2 —冷流体出口处冷流体侧的壁面温度，C。热、冷流体间的对数平均温差可由式（ 4 —4）计算, 当在套管式间壁换热器中，环隙通以水蒸气，内管管内通以冷空气或水进行对流传热系数测定实验时，则由式（4—1）得内管内壁面与冷空气或水的对流传热系数, 叫*-片） (4-5) 实验中测定紫铜管的壁温t wi、t w2；冷空气或水的进出口温度t l、t2；实验用紫铜管的 (4-4 )

化工原理实验报告实验三传热膜系数测定实验实验日期：2015年12月30日班级：学生姓名：学号：同组人：报告摘要本实验选用牛顿冷却定律作为对流传热实验的测试原理,通过建立不同体系的传热系统,即水蒸汽—空气传热系统、分别对普通管换热器和强化管换热器进行了强制对流传热实验研究。确定了在相应条件下冷流体对流传热膜系数的关联式。此实验方法可以测出蒸汽冷凝膜系数和管内对流传热系数。采用由风机、孔板流量计、蒸汽发生器等组成的自动化程度较高的装置，让空气走内管，蒸汽走环隙，用计算机在线采集与控制系统测量了孔板压降、进出口温度和两个壁温，计算了传热膜系数α，并通过作图确定了传热膜系数准数关系式中的系数A 和指数m （n 取0.4），得到了半经验关联式。实验还通过在内管中加入混合器的办法强化了传热，并重新测定了α、A 和m 。二、目的及任务 1.掌握传热膜系数α及传热系数K 的测定方法； 2.通过实验掌握确定传热膜系数准数关系式中的系数A 和指数m 的方法； 3.了解工程上强化传热的措施。三、基本原理对流传热的核心问题是求算传热膜系数α，当流体无相变时对流传热准数关系式的一般形式为：p n m Gr A Nu Pr Re 对于强制湍流而言。Gr 数可忽略，即

n m A Nu Pr Re = 本实验中，可用图解法和最小二乘法计算上述准数关系式中的指数m 、n 和系数A 。用图解法对多变量方程进行关联时，要对不同变量Re 和Pr 分别回归。本实验可简化上式，即取n=0.4(流体被加热)。这样，上式即变为单变量方程，在两边取对数，得到直线方程为 Re lg lg Pr lg 4.0m A Nu += 在双对数坐标中作图，求出直线斜率，即为方程的指数m 。在直线上任取一点函数值带入方程中，则可得系数A ，即 m Nu A Re Pr 4.0= 用图解法，根据实验点确定直线位置有一定人为性。而用最小二乘法回归，可得到最佳关联结果。应用计算机辅助手段，对多变量方程进行一次回归，就能的道道A 、m 、n 。对于方程的关联，首先要有Nu 、Re 、Pr 的数据组。其特征数定义式分别为 μρ du = Re ， λμ Cp = Pr ， λαd Nu = 实验中改变空气的流量，以改变Re 值。根据定性温度(空气进、出口温度的算数平均值)计算对应的Pr 值。同时，由牛顿冷却定律，求出不同流速下的传热膜系数值，进而求得Nu 值。牛顿冷却定律为 Q=αA △t m 式中α——传热膜系数，W/(m 2.℃)；

淘宝运营的所有相关指标【基础统计类】 1、浏览量（PV）：店铺各页面被查看的次数。用户多次打开或刷新同一个页面，该指标值累加。 2、访客数(UV)：全店各页面的访问人数。所选时间段内，同一访客多次访问会进行去重计算。 3、收藏量：用户访问店铺页面过程中，添加收藏的总次数（包括首页、分类页和宝贝页的收藏次数）。 4、浏览回头客：指前6天内访问过店铺当日又来访问的用户数，所选时间段内会进行去重计算。 5、浏览回头率：浏览回头客占店铺总访客数的百分比。 6、平均访问深度：访问深度，是指用户一次连续访问的店铺页面数（即每次会话浏览的页面数），平均访问深度即用户平均每次连续访问浏览的店铺页面数。【月报-店铺经营概况】中，该指标是所选月份日数据的平均值。 7、跳失率：表示顾客通过相应入口进入，只访问了一个页面就离开的访问次数占该入口总访问次数的比例。 8、人均店内停留时间（秒）：所有访客的访问过程中，平均每次连续访问店铺的停留时间。 9、宝贝页浏览量：店铺宝贝页面被查看的次数，用户每打开或刷新一个宝贝页面，该指标就会增加。 10、宝贝页访客数：店铺宝贝页面的访问人数。所选时间段内，同一访客多次访问会进行去重计算。 11、宝贝页收藏量：用户访问宝贝页面添加收藏的总次数。 12、入店页面：单个用户每次浏览您的店铺时查看的第一个页面为入店页面。出店页面：单个用户每次浏览您店铺时所查看的最后一个页面为出店页面。 13、入店人次：指从该页面进入店铺的人次。 14、出店人次：指从该页面离开店铺的人次 15、进店时间：用户打开该页面的时间点，如果用户刷新页面，也会记录下来。

16、停留时间：用户打开本店最后一个页面的时间点减去打开本店第一个页面的时间点（只访问一页的顾客停留时间暂无法获取，这种情况不统计在内，显示为“—”）。 17、到达页浏览量：到达店铺的入口页面的浏览量。 18、平均访问时间：打开该宝贝页面到打开下一个宝贝页面的平均时间间隔。（用户访问该宝贝页后，未点击该页其他链接的情况不统计在内，显示为“—”） 19、全店宝贝查看总人次：指全部宝贝的查看人次之和。 20、搜索次数：在店内搜索关键词或价格区间的次数。【销售分析类】 1、拍下件数：宝贝被拍下的总件数。 2、拍下笔数：宝贝被拍下的总次数（一次拍下多件宝贝，算拍下一笔）。 3、拍下总金额：宝贝被拍下的总金额。 4、成交用户数：成功拍下并完成支付宝付款的人数。所选时间段内同一用户发生多笔成交会进行去重计算。 5、成交回头客：曾在店铺发生过交易，再次发生交易的用户称为成交回头客。所选时间段内会进行去重计算。 6、支付宝成交件数：通过支付宝付款的宝贝总件数。 7、支付宝成交笔数：通过支付宝付款的交易总次数（一次交易多件宝贝，算成交一笔）。 8、支付宝成交金额：通过支付宝付款的金额。 9、人均成交件数：平均每用户购买的宝贝件数，即人均成交件数= 支付宝成交件数/ 成交用户数。 10、人均成交笔数：平均每用户购买的交易次数，即人均成交笔数= 支付宝成交笔数/ 成交用户数。 11、当日拍下-付款件数：当日拍下、且当日通过支付宝付款的宝贝件数。 12、当日拍下-付款笔数：当日拍下、且当日通过支付宝付款的交易次数。 13、当日拍下-付款金额：当日拍下、且当日通过支付宝付款的金额。

传热综合实验实验

传热综合实验实验数据记录与处理 1.原始数据记录表格以下计算以次序1作为计算实例：空气进口密度52310 4.510 1.2916t t ρ--=-?+=10-5*48.4 2 -4.5*10-3 *48.4+1.2916=1.053 kg/m 3；空气质量流量m s2 =ρV=1.053*46.286/3600=0.0135kg/s ；空气流速u=4V/(πd 2)=4*46.286/(3.14*0.02*0.02*3600)=40.95 m/s ；空气定性温度(t 1+t 2)/2=(48.4+82.7)/2=65.55℃；换热面积22A d l π== 3.14*0.016*1=0.0502m 2；空气的比热 C p2=1005 J / (kg ?℃)；对数平均温度 ()()1 2211221ln t T t T t T t T t m -----= ?=33.001℃；

总给热系数 ()m p t A t t c m K ?-= 1222=0.25933 W/(m 2·℃)； 2.计算结果列表密度52310 4.510 1.2916t t ρ--=-?+=10-5*50.252 -4.5*10-3 *50.25+1.2916=1.09kg/m 3 流体粘度6235(210510 1.716910t t μ---=-?+?+?） =6235(210*50.25510*50.25 1.716910----?+?+?） =1.96E-05 Pa ·s ； t=定性温度；流体导热系数8252108100.0244t t λ--=-?+?+ =825210*50.25810*50.250.0244---?+?+= 0.0284 W/(m ·℃)；雷诺准数μ ρ du =Re =0.016*7.19*1.09/1.96E-05=6397.63；普兰特数 λ μ 2Pr p c = =(1005*1.96E-05)/ 0.0284=0.694；理论值 α=4.08.0Pr Re 023.0d λ =0.80.40.0284 0.023*6397.630.6940.016 =39.11 W/(m 2·℃)；努赛尔数λ αd Nu = = 39.11*0.016/0.0284=22.03。

套管换热器传热实验实验报告数据处理我们组做的是实验I : 1， Q=m s1c 1 △t 1 求K 得先求Q Q=m s 1C 1△t 1 ,其中，C 1=所以得先求m s 1 , C 1， △t 1, ◇ 1m s1 =V s1 ρ 要得求V s1，V s1=u 1A ，V s1 =C 0A 0ρρρ/o (2）-gR C 0为空流系数，C 0=0.855,A 0为空口面积，A 0的计算方法如下：A 0 =π4 d 02 , d 0=20.32 mm,故 A 0= π4 ×（20.32 1000 ）2=3.243293×10-4 m 2 R 为压计差读数 A=π4 d 2 ,d 为内管内径=20mm ，用内插法求解空气密度 ρ 值这样求得m s 1， ◇ 2 C 1 的求法为先查表的相近温度下空气的C 值，然后用内插法求得对应平均温度对应的的C 1值 ◇ 3 求△t 1= t △ t 1 ,= t = t 1 + t 2 2 t 1 为进口温度 t 2 为出口温度进口温度t 1的求解方法由热电偶中的电位Vt ，按照公式求[]2 000000402.00394645.0t t V E t t ++=得

Et ，再由852.4901004.810608.1105574.15 43-??+?=---t E t 求得t 1值出口温度t 2的求解方法由热电偶中的电位Vt ，按照公式[]2 000000402.00394645.0t t V E t t ++=求得 Et ，再由852.49010 04.810608.1105574.15 43-??+?=---t E t 求得t 2值由以上步骤求出 Q 2 ，由Q=KA △t m 求出K 值 K= Q A △t m Q 由第一步已经求出，A 为内管内径对应的面积，A=2π rL ,r=17.8mm=0.0178 m, A=2×3.14×0.0178×1.224=0.13682362 m 2 3 ,求Re ，Nu 流体无相变强制湍流经圆形直管与管壁稳定对流传热时，对流传热准数关联式的函数关系为： (,,)l Nu f Re Pr d = 对于空气，在实验范围内，Pr 准数基本上为一常数；当管长与管径的比值大于50 时，其值对 Nu 的影响很小；则 Nu 仅为 Re 的函数，故上述函数关系一般可以处理成： m Nu aRe = 式中，a 和 m 为待定常数。 Re=du ρ μ d=2×0.0178 m =0.0356 m , u=Vs/（π×0.01782 ）μ 和ρ用内插法，先查表的相近温度的μ，ρ，再用线性关系计算求得。测量空气一侧管壁的中区壁温T W ，由热电偶按前面公式求得；由下式可以计算空气与管壁

传热综合实验实验内部编号：（YUUT-TBBY-MMUT-URRUY-UOOY-DBUYI-0128）

换热面积22A d l π== 3.14*0.016*1=0.0502m 2；空气的比热 C p2=1005 J / (kg ℃)；对数平均温度 ()()1 2211221ln t T t T t T t T t m -----= ?=33.001℃；总给热系数 ()m p t A t t c m K ?-=1222=0.25933 W/(m 2·℃)； 2.计算结果列表密度52310 4.510 1.2916t t ρ--=-?+=10-5 *50.252 -4.5*10-3 *50.25+1.2916=1.09kg/m 3 流体粘度6235(210510 1.716910t t μ---=-?+?+?） =6235(210*50.25510*50.25 1.716910----?+?+?） =1.96E-05 Pa ·s ； t=定性温度；

淘宝数据【基础统计类】 1、浏览量（PV）：店铺各页面被查看的次数。用户多次打开或刷新同一个页面，该指标值累加。 2、访客数(UV)：全店各页面的访问人数。所选时间段内，同一访客多次访问会进行去重计算。 3、收藏量：用户访问店铺页面过程中，添加收藏的总次数（包括首页、分类页和宝贝页的收藏次数）。 4、浏览回头客：指前6天内访问过店铺当日又来访问的用户数，所选时间段内会进行去重计算。 5、浏览回头率：浏览回头客占店铺总访客数的百分比。 6、平均访问深度：访问深度，是指用户一次连续访问的店铺页面数（即每次会话浏览的页面数），平均访问深度即用户平均每次连续访问浏览的店铺页面数。【月报-店铺经营概况】中，该指标是所选月份日数据的平均值。 7、跳失率：表示顾客通过相应入口进入，只访问了一个页面就离开的访问次数占该入口总访问次数的比例。 8、人均店内停留时间（秒）：所有访客的访问过程中，平均每次连续访问店铺的停留时间。 9、宝贝页浏览量：店铺宝贝页面被查看的次数，用户每打开或刷新一个宝贝页面，该指标就会增加。 10、宝贝页访客数：店铺宝贝页面的访问人数。所选时间段内，同一访客多次访问会进行去重计算。 11、宝贝页收藏量：用户访问宝贝页面添加收藏的总次数。 12、入店页面：单个用户每次浏览您的店铺时查看的第一个页面为入店页面。出店页面：单个用户每次浏览您店铺时所查看的最后一个页面为出店页面。 13、入店人次：指从该页面进入店铺的人次。 14、出店人次：指从该页面离开店铺的人次。 15、进店时间：用户打开该页面的时间点，如果用户刷新页面，也会记录下来。 16、停留时间：用户打开本店最后一个页面的时间点减去打开本店第一个页面的时间点（只访问一页的顾客停留时间暂无法获取，这种情况不统计在内，显示为“—”）。 17、到达页浏览量：到达店铺的入口页面的浏览量。 18、平均访问时间：打开该宝贝页面到打开下一个宝贝页面的平均时间间隔。（用户访问该宝贝页后，未点击该页其他链接的情况不统计在内，显示为“—”） 19、全店宝贝查看总人次：指全部宝贝的查看人次之和。 20、搜索次数：在店内搜索关键词或价格区间的次数。【销售分析类】 1、拍下件数：宝贝被拍下的总件数。 2、拍下笔数：宝贝被拍下的总次数（一次拍下多件宝贝，算拍下一笔）。 3、拍下总金额：宝贝被拍下的总金额。 4、成交用户数：成功拍下并完成支付宝付款的人数。所选时间段内同一用户发生多笔成交会进行去重计算。

淘宝运营的所有相关

淘宝运营的所有相关指标【基础统计类】 1、浏览量（PV）:店铺各页面被查看的次数。用户多次打开或刷新同一个页面，该指标值累加。 2、访客数（UV）:全店各页面的访问人数。所选时间段内，同一访客多次访问会进行去重计算。 3、收藏量：用户访问店铺页面过程中，添加收藏的总次数（包括首页、分类页和宝贝页的收藏次数）。 4、浏览回头客：指前6天内访问过店铺当日又来访问的用户数，所选时间段内会进行去重计算。 5、浏览回头率：浏览回头客占店铺总访客数的百分比。 &平均访问深度：访问深度，是指用户一次连续访问的店铺页面数（即每次会话浏览的页面数），平均访问深度即用户平均每次连续访问浏览的店铺页面数。【月报-店铺经营概况】中，该指标是所选月份日数据的平均值。 7、跳失率：表示顾客通过相应入口进入，只访问了一个页面就离开的访问次数占该入口总访问次数的比例。 8、人均店内停留时间（秒）：所有访客的访问过程中，平均每次连续访问店铺的停留时间。 9、宝贝页浏览量：店铺宝贝页面被查看的次数，用户每打开或刷新一个宝贝页面，该指标就

会增加。 10、宝贝页访客数：店铺宝贝页面的访问人数。所选时间段内，同一访客多次访问会进行去重计算。 11、宝贝页收藏量：用户访问宝贝页面添加收藏的总次数。 12、入店页面：单个用户每次浏览您的店铺时查看的第一个页面为入店页面。出店页面：单个用户每次浏览您店铺时所查看的最后一个页面为出店页面。 13、入店人次：指从该页面进入店铺的人次。 14、出店人次：指从该页面离开店铺的人次 15、进店时间：用户打开该页面的时间点，如果用户刷新页面，也会记录下来。 16、停留时间：用户打开本店最后一个页面的时间点减去打开本店第一个页面的时间点（只访问一页的顾客停留时间暂无法获取，这种情况不统计在内，显示为“一”）。 17、到达页浏览量：到达店铺的入口页面的浏览量。 18、平均访问时间：打开该宝贝页面到打开下一个宝贝页面的平均时间间隔。（用户访问该宝贝页后，未点击该页其他链接的情况不统计在内，显示为“一 ”） 19、全店宝贝查看总人次：指全部宝贝的查看人次之和。

实验五传热综合实验一、实验目的 1.通过对空气—水蒸气简单套管换热器的实验研究，掌握对流传热系数i α的测定方法，加深对其概念和影响因素的理解。并应用线性回归分析方法，确定关联式Nu=ARe m Pr 0.4中常数A 、m 的值。 2.通过对管程内部插有螺旋线圈的空气—水蒸气强化套管换热器的实验研究，测定其准数关联式Nu=BRe m 中常数B 、m 的值和强化比Nu/Nu 0，了解强化传热的基本理论和基本方式。二、实验内容 1. 测定5～6个不同流速下普通套管换热器的对流传热系数i α，对i α的实验数据进行线性回归，求关联式Nu=ARe m Pr 0.4中常数A 、m 的值。 2.测定5～6个不同流速下强化套管换热器的对流传热系数i α，对i α的实验数据进行线性回归，求关联式Nu=BRe m 中常数B 、m 的值。 3.同一流量下，按实验1所得准数关联式求得Nu 0，计算传热强化比Nu/Nu 0。三、实验原理（一）普通套管换热器传热系数及其准数关联式的测定 1.对流传热系数i α的测定对流传热系数i α可以根据牛顿冷却定律，用实验来测定。因为i α<