温度曲线
- 格式:pdf
- 大小:762.05 KB
- 文档页数:10
温度循环曲线(原创实用版)目录一、引言二、温度循环曲线的定义和作用1.定义2.作用三、温度循环曲线的分类1.温度循环曲线的类型2.各类温度循环曲线的特点四、温度循环曲线的应用1.在工业生产中的应用2.在科研中的应用五、结论正文一、引言在工业生产和科研领域中,对温度的控制是一个非常重要的环节。
温度的波动会直接影响到产品的质量、生产效率以及设备的使用寿命。
因此,研究温度变化规律,对于优化生产过程、提高产品质量具有重要意义。
温度循环曲线就是描述温度随时间变化的一种曲线,它可以帮助我们了解温度变化的规律,从而更好地指导生产和科研活动。
二、温度循环曲线的定义和作用1.定义温度循环曲线,又称温度波动曲线,是指在一个特定的时间范围内,温度随时间变化的轨迹。
它可以显示温度的最高值、最低值以及平均值,有助于分析温度变化的规律。
2.作用温度循环曲线在工业生产和科研中有着重要的作用,主要体现在以下几个方面:(1) 分析温度波动的原因:通过观察温度循环曲线,可以了解温度波动的原因,如设备故障、生产过程不稳定等,从而及时采取措施,保证生产正常进行。
(2) 优化生产过程:根据温度循环曲线,可以了解生产过程中的温度变化规律,从而调整生产参数,提高生产效率。
(3) 保证产品质量:温度是影响产品质量的一个重要因素,通过分析温度循环曲线,可以确保产品在适宜的温度范围内生产,从而提高产品质量。
三、温度循环曲线的分类1.温度循环曲线的类型根据不同的应用场景,温度循环曲线可以分为以下几种类型:(1) 连续式温度循环曲线:连续式温度循环曲线是指在一段时间内,温度随时间连续变化的曲线。
(2) 间歇式温度循环曲线:间歇式温度循环曲线是指在生产过程中,设备间歇运行时,温度随时间变化的曲线。
(3) 瞬时式温度循环曲线:瞬时式温度循环曲线是指在某一特定时刻,温度随时间变化的曲线。
2.各类温度循环曲线的特点(1) 连续式温度循环曲线:连续式温度循环曲线具有连续性、平稳性等特点,适用于连续生产过程。
年温度变化曲线
年温度变化曲线是表示一年内气温变化的曲线图。
通常,这种曲线图以时间为横轴,以温度为纵轴,通过连接每日、每月或每年的平均气温值而形成的连续曲线。
这种曲线图可以直观地展示一年内气温的波动和变化趋势。
通过年温度变化曲线,可以观察到以下现象和规律:
1. 季节变化:曲线在一年中会呈现出明显的波峰和波谷,分别对应着夏季和冬季的气温高低。
在温带地区,夏季气温较高,冬季气温较低,而春秋两季则为过渡季节,气温适中。
2. 昼夜温差:在一天之内,气温也会有所波动。
通常在日出后,随着太阳辐射的增强,气温逐渐升高,到午后达到最高值;随后随着太阳辐射的减弱,气温逐渐降低,到次日日出前达到最低值。
这种昼夜温差在曲线图上可能表现为微小的波动。
3. 异常天气:某些极端天气事件,如寒潮、热浪等,会在曲线图上表现为异常的气温波动。
例如,寒潮来临时,气温会骤降,曲线图上会出现一个向下的尖峰;而热浪则会使得气温异常升高,形成一个向上的尖峰。
4. 气候类型:不同的气候类型具有不同的年温度变化曲线特征。
例如,热带气候的气温变化较小,曲线相对平缓;而温带气候的气温变化较大,曲线波动明显。
通过分析和比较不同地区的年温度变化曲线,可以了解不同气候类型的特征以及气候变化对人类社会和自然环境的影响。
温度曲线的原理与应用1. 温度曲线的原理温度曲线是指随着时间的推移,温度值的变化情况在坐标系内形成的曲线。
温度曲线的绘制是通过测量和记录不同时间点的温度值来实现的。
它可以帮助我们了解物体的温度变化趋势,从而更好地理解物体的特性和性能。
1.1 温度传感器的原理温度传感器是测量温度的工具,可以将温度值转化为电信号。
常见的温度传感器有热电偶、热敏电阻、半导体温度传感器等。
它们的工作原理各不相同,但都基于物质的热力学性质,利用热量与电信号之间的相互转换来实现温度测量。
1.2 温度曲线的绘制方法绘制温度曲线的方法通常是将时间作为横轴,将温度值作为纵轴。
通过将不同时间点的温度值连接起来,可以得到温度随时间变化的曲线。
在绘制温度曲线时,通常需要选择合适的坐标轴范围和刻度值,以便更清楚地显示温度变化的趋势。
2. 温度曲线的应用温度曲线在许多领域都有广泛的应用。
以下列举了一些常见的应用场景:2.1 环境监测温度曲线在环境监测中起着重要的作用。
通过监测和记录环境中的温度变化,我们可以了解气候变化、季节变化以及人类活动对环境温度的影响。
这对于研究气候变化、环境管理等方面具有重要意义。
2.2 工业控制在工业生产中,温度曲线被广泛应用于工艺控制和质量监测。
通过监测生产过程中的温度变化,可以及时发现并解决温度异常问题,以确保产品的质量和生产效率。
2.3 医疗诊断温度曲线在医疗诊断中也有重要的应用。
例如,在体温检测中,通过记录患者的体温值并绘制温度曲线,医生可以了解患者的体温变化趋势,以便判断患者是否发烧或存在其他健康问题。
2.4 热力学研究温度曲线在热力学研究中是一个重要的工具。
通过记录材料或化学反应过程中的温度变化,可以推断出反应的放热或吸热性质,从而对反应过程进行分析和优化。
2.5 设备监控温度曲线还可以用于设备监控。
例如,在机械设备或电子设备中,通过监测设备的温度变化,可以及时发现设备故障或过热问题,并采取相应的措施来防止设备损坏或故障。
温度时间曲线一、引言温度时间曲线是指在一定时间范围内,物体的温度随时间变化的图像表现形式。
它是研究物体温度变化规律的重要工具,广泛应用于工业、农业、医学等领域。
二、温度时间曲线的构成温度时间曲线由横轴和纵轴组成。
横轴一般表示时间,纵轴表示温度。
在曲线上,不同颜色或样式的线条可以代表不同物体或不同时期的数据。
三、温度时间曲线的应用1. 工业领域在工业生产过程中,对于某些需要控制温度的产品或设备,通过绘制温度时间曲线可以及时发现异常情况并采取相应措施。
在钢铁生产过程中,通过绘制钢水冷却曲线可以判断钢水是否达到了合适的浇注温度。
2. 农业领域在农业生产中,通过绘制土壤或气象站点的温度变化曲线可以预测作物生长情况,并采取相应措施以提高作物产量。
3. 医学领域在医学领域中,温度时间曲线也被广泛应用于疾病诊断和治疗过程中。
在发热患者的体温测量中,绘制体温时间曲线可以帮助医生判断患者是否需要进行进一步检查或治疗。
四、温度时间曲线的绘制方法1. 数据采集在绘制温度时间曲线之前,需要先采集相应的数据。
数据可以通过传感器、记录仪等设备获取,也可以手动记录。
2. 数据处理将采集到的数据进行处理,包括去除异常值、平滑处理等。
同时,还需要将数据按照一定的时间间隔进行分组。
3. 绘制曲线根据处理后的数据,使用专业软件或手工绘制出温度时间曲线,并标注相应的轴标签和图例。
五、常见的温度时间曲线类型1. 单峰型单峰型温度时间曲线是指物体在某一时刻达到最高温度后逐渐降低至环境温度。
这种类型的曲线常见于许多工业生产过程中。
2. 双峰型双峰型温度时间曲线是指物体在某一时刻达到第一个高峰温度后稍有下降,然后再次升高并达到第二个高峰温度。
这种类型的曲线常见于化学反应过程中。
3. 上升型上升型温度时间曲线是指物体的温度随时间逐渐升高,但没有达到峰值。
这种类型的曲线常见于许多生物学实验中。
4. 下降型下降型温度时间曲线是指物体的温度随时间逐渐下降,但没有达到最低点。
温度循环曲线
摘要:
1.温度循环曲线的定义和作用
2.温度循环曲线的绘制方法
3.温度循环曲线的应用领域
4.温度循环曲线的意义和价值
正文:
温度循环曲线是一种用于描述物体在温度变化过程中温度随时间变化的曲线。
通常情况下,温度循环曲线是以时间为横坐标,温度为纵坐标,绘制出的一条曲线。
温度循环曲线的绘制方法可以根据实际需要选择不同的温度变化范围和时间间隔。
温度循环曲线在工程领域中有着广泛的应用。
例如,在材料科学中,可以通过绘制温度循环曲线来研究材料的疲劳寿命和耐久性能;在机械工程中,可以通过分析温度循环曲线来预测设备的故障和损坏情况;在航空航天领域,温度循环曲线则是研究飞行器的热保护系统的重要依据。
温度循环曲线不仅能够反映物体的温度变化情况,还能够揭示物体的热传导性能和热稳定性。
因此,对于工程设计和运行维护来说,准确地绘制和分析温度循环曲线具有重要的意义和价值。
24小时气温变化曲线标题:24小时气温变化曲线概述:本文将以24小时为单位,探讨气温的变化曲线。
通过分析不同时间段内的气温波动情况,展示气温的变化规律,以期帮助读者更好地了解天气变化。
1. 温暖的早晨(06:00 – 09:00)早晨是一天中气温相对较低的时段,特别是在日出后。
在06:00-07:00期间,气温通常处于较低点,平均在10℃以下。
随着时间的推移,气温逐渐升高,在08:00-09:00间可能达到15℃左右。
这个时间段通常是人们出行上班的时间,需要注意保暖措施。
2. 白天升温(09:00 – 15:00)早晨过后,气温开始迅速上升。
在09:00-12:00期间,气温可能会急剧升高,超过20℃。
这是白天最炎热的时段,人们需要防晒和补水。
下午12:00-15:00之间,气温可能会稍有下降,但仍保持在较高水平。
3. 午后的小幅变化(15:00 – 18:00)15:00-18:00期间,气温可能会出现小幅波动,但整体上保持相对稳定。
这个时间段通常是人们下班后的休闲时间,适合户外活动。
气温一般在20℃左右,但在特殊情况下,如夏季高温天气,可能会超过30℃。
4. 黄昏渐凉(18:00 – 21:00)18:00-21:00期间,气温逐渐下降,但仍保持在较为宜人的水平。
通常在这个时间段,气温会从25℃左右逐渐降至20℃以下。
人们可以感受到天气的变凉,适宜散步和户外聚会。
5. 夜晚的温凉(21:00 – 06:00)夜晚是一天中气温最低的时段。
21:00-24:00间,气温可能会降至15℃以下。
在凌晨时段(00:00-06:00),气温会进一步下降,常常在10℃以下。
此时,人们需要注意保暖,穿上合适的衣物。
总结:通过以上分析,我们可以看出24小时内气温的变化曲线。
早晨气温较低,白天最炎热,下午稍有回落,黄昏温度适宜,夜晚气温最低。
了解气温的变化规律,可以帮助我们合理安排日常生活和活动,为健康和舒适提供参考依据。
导热系数随温度变化曲线
导热系数随温度变化的曲线称为热导率-温度曲线。
一般来说,不同物质的热导率都会随温度的变化而发生变化。
然而,不同物质的热导率-温度曲线可能有所不同,因为它们的物理性质和结构不同。
一些物质的热导率随温度的上升而增加,这种物质被称为正温度系数导体。
例如,金属通常在较高温度下具有较高的热导率。
另一些物质的热导率随温度的上升而减小,这种物质被称为负温度系数导体。
例如,某些半导体材料在较高温度下具有较低的热导率。
除了正温度系数和负温度系数导体外,还有一些物质的热导率随温度的变化呈现复杂的曲线。
例如,一些材料在特定温度范围内有最高的热导率,称为热导率极大值。
总之,不同物质的热导率-温度曲线各不相同,具体取决于物质的性质和结构。
如果需要具体的热导率-温度曲线,需要参考具体物质的热学性质数据表或相关研究文献。
温度循环曲线温度循环曲线是指物体或系统在一定时间范围内温度随时间的变化过程所形成的曲线。
它反映了物体或系统从起始温度到最终温度再回到起始温度的完整循环变化,以及在循环过程中的温度变化规律。
温度循环曲线在材料研究、能源管理、环境监测等领域中具有重要的应用价值。
温度循环曲线可以分为两种类型:周期性温度循环曲线和非周期性温度循环曲线。
周期性温度循环曲线是指温度以相同的周期在一定范围内循环变化,如恒温器的工作原理中的温度循环。
非周期性温度循环曲线是指温度以不同的周期在一定范围内循环变化,如太阳辐射引起的地球表面温度变化。
温度循环曲线的形状和特点受多种因素影响,包括外部环境条件、物体或系统的属性以及实验或观测的时间范围等。
一般来说,温度循环曲线可以分为上升段、保持段和下降段。
上升段是指物体或系统温度逐渐升高的过程,保持段是指物体或系统温度在一定范围内稳定保持不变的过程,下降段是指物体或系统温度逐渐降低的过程。
在周期性温度循环曲线中,上升段和下降段一般为对称的,即温度的变化速率相同且温度变化规律相似。
而保持段则是温度保持在稳定值的过程,时间长度和温度幅度一般是由外部控制条件决定的。
在非周期性温度循环曲线中,上升段和下降段的形状和特点可能会有较大的差异,因为温度的变化受多种因素的影响。
例如,太阳辐射引起的地球表面温度变化,由于日照时间、气象条件和地理位置的差异,导致温度循环曲线的形状和特点不同。
温度循环曲线的研究对于了解物体或系统的热力学性质、优化工艺参数以及提高能源利用效率具有重要意义。
通过分析温度循环曲线可以确定温度变化的趋势和时间尺度,从而选择合适的温度控制策略和优化工艺流程。
此外,温度循环曲线也可以用于环境监测和气候变化研究中,帮助科学家了解地球气候系统的变化规律和趋势。
总之,温度循环曲线是物体或系统温度随时间的变化过程所形成的曲线,反映了物体或系统的温度变化规律。
它在材料研究、能源管理、环境监测等领域中具有重要的应用价值。
tec温度曲线摘要:1.TEC温度曲线简介2.TEC温度曲线的作用与意义3.如何在实际应用中利用TEC温度曲线4.TEC温度曲线的案例分析5.总结与展望正文:一、TEC温度曲线简介TEC(Temperature Encoding Curve)温度曲线是一种将温度信息编码成可视化曲线的技术。
通过对温度进行编码,可以使温度变化以更加直观的方式呈现出来。
TEC温度曲线在许多领域都有广泛的应用,如气象、地质、环境监测等。
二、TEC温度曲线的作用与意义1.直观反映温度变化:TEC温度曲线将温度数据以图形的形式展示,使观察者能够一目了然地了解温度波动情况。
2.便于数据分析:TEC温度曲线为温度数据的分析和处理提供了便捷的方式,可以快速发现温度变化的规律和趋势。
3.预测温度趋势:基于TEC温度曲线,可以对未来一段时间的温度变化进行预测,为决策者提供依据。
4.科学研究与教育:TEC温度曲线在科学研究和教育领域具有较高的实用价值,有助于普及温度相关知识。
三、如何在实际应用中利用TEC温度曲线1.采集温度数据:首先需要对所需研究的对象进行温度数据的采集,可以使用各种温度传感器实现。
2.数据处理:将采集到的温度数据进行预处理,如去除异常值、平滑滤波等,以提高数据的准确性。
3.绘制TEC温度曲线:利用数据分析软件或编程语言(如Python、R 等)将处理后的温度数据绘制为TEC温度曲线。
4.分析与解读:根据TEC温度曲线,对其中的温度变化规律、波动原因等进行分析和解读。
5.应用实践:将TEC温度曲线应用于实际问题中,如节能减排、农业生产、疾病防控等。
四、TEC温度曲线的案例分析以下是一个简单的案例:某农业园区想要了解温室内部的温度变化,以优化温室环境,提高农作物产量。
通过在温室中安装温度传感器,采集实时温度数据,并绘制TEC温度曲线。
分析曲线发现,白天温度较高,夜间温度较低,且在凌晨时分存在温度低谷。
根据这一特点,园区管理人员可以调整温室通风、遮阳等策略,以保持适宜的温度环境,促进农作物生长。
温度曲线1. 引言温度曲线是描述一段时间内温度变化的图表。
它可以展示不同地区、不同季节、不同天气条件下的温度变化趋势。
通过分析温度曲线,我们可以了解天气变化、气候模式以及环境变化对温度的影响。
温度曲线也被广泛用于天气预报、气候研究、农业生产等领域。
2. 温度曲线的构成温度曲线通常由时间和温度两个变量组成。
时间通常以横轴表示,温度则以纵轴表示。
温度曲线以点的形式组成,这些点通过直线或曲线相连,最终形成一个连续的曲线。
3. 温度曲线的图表形式3.1 折线图折线图是最常见的温度曲线图表形式之一。
它通过将时间和温度变量绘制在坐标轴上,然后用直线段连接各个点,形成一条折线。
折线图清晰地展示了温度变化的趋势,可以帮助我们快速了解温度的变化情况。
3.2 面积图面积图也是常见的温度曲线图表形式之一。
它在折线图的基础上,将折线以下的区域填充颜色,形成一个封闭的面积。
面积图可以更直观地展示温度的变化范围,帮助我们更清楚地看出温度的波动情况。
3.3 热力图热力图是一种基于色彩来表达数据的图表形式。
在温度曲线中,热力图可以将不同温度区间设置为不同的颜色,通过颜色的深浅变化来展示温度的变化情况。
热力图可以直观地反映不同地区的温度差异以及温度分布的规律。
4. 温度曲线的应用4.1 天气预报温度曲线是天气预报中常用的工具之一。
通过观察温度曲线,我们可以了解未来几天的温度变化趋势,预测天气的变化情况。
天气预报部门根据温度曲线提供准确的天气预报,帮助人们合理安排活动和出行计划。
4.2 气候研究温度曲线对于气候研究也具有重要意义。
通过观察长时间的温度曲线,科学家可以分析气候的周期性变化、长期趋势以及其对环境的影响。
温度曲线是了解气候变化的重要工具,为气候模式的建立和改进提供了数据支持。
4.3 农业生产温度曲线对农业生产也有直接的影响。
不同作物对温度有不同的要求,温度的变化会影响作物的生长和产量。
通过观察温度曲线,农民可以合理安排种植时间,调整农业措施,提高农作物的产量和质量。
温度循环曲线摘要:一、引言二、温度循环曲线的定义与作用三、温度循环曲线的绘制方法四、温度循环曲线在工程领域的应用五、温度循环曲线对我国经济发展的影响六、结论正文:一、引言温度循环曲线是一种描述物体在温度变化过程中温度随时间变化的曲线。
在科学研究和工程实践中,温度循环曲线对于分析材料的性能、评估设备的运行状况具有重要意义。
本文将详细介绍温度循环曲线的相关知识,包括定义、绘制方法以及在工程领域的应用。
二、温度循环曲线的定义与作用温度循环曲线是指在一定时间内,物体经历多次温度变化后,温度随时间变化的曲线。
通常情况下,温度循环曲线包括上升段、稳定段和下降段。
通过分析温度循环曲线,我们可以了解材料在不同温度下的性能变化,为材料选择和工程设计提供依据。
三、温度循环曲线的绘制方法绘制温度循环曲线的方法有多种,常见的有恒定应力法、恒定应变法和恒定温度法。
其中,恒定应力法适用于高温下材料的性能研究;恒定应变法适用于低温下材料的性能研究;恒定温度法适用于常温下材料的性能研究。
在实际操作中,根据不同的应用需求选择合适的绘制方法。
四、温度循环曲线在工程领域的应用温度循环曲线在工程领域具有广泛的应用,如航空航天、汽车制造、建筑材料等。
通过分析温度循环曲线,工程师可以评估设备的运行状况,为设备维护和优化设计提供依据。
同时,温度循环曲线还可以指导材料的选用,提高工程质量和经济效益。
五、温度循环曲线对我国经济发展的影响温度循环曲线对我国经济发展具有积极影响。
在制造业、建筑业等领域,通过研究温度循环曲线,可以提高产品的质量和性能,降低设备故障率,提高生产效率。
此外,在新能源、节能减排等领域,温度循环曲线的研究也有助于推动技术创新,促进绿色经济发展。
六、结论温度循环曲线是描述物体在温度变化过程中温度随时间变化的重要工具,对于科学研究和工程实践具有重要意义。
温度曲线波动大的原因概述说明以及解释1. 引言1.1 概述温度曲线波动是指气候或季节内温度变化的周期性、季节性和随机性特征。
随着科技的进步和全球气候变暖的影响,人们对温度曲线波动的了解越来越重要。
本文旨在概述温度曲线波动大的原因,并详细说明和解释这些原因。
1.2 文章结构本文分为五个部分:引言、温度曲线波动大的原因、温度曲线波动的概述说明、温度曲线波动的解释以及结论与总结。
接下来将按照该结构逐一介绍相关内容。
1.3 目的本文的目标是系统地探讨导致温度曲线波动大的各种原因,包括自然因素、人为因素以及综合影响因素,并从大气环流系统影响、上层风场活动影响和地表能量平衡调节影响等方面对温度曲线波动进行解释。
通过深入分析,我们可以更好地理解影响和导致高幅度温度变化相关问题,以期为未来的研究和气候变化的应对提供参考依据。
2. 温度曲线波动大的原因2.1 自然因素温度曲线的波动受到多个自然因素的影响。
首先,气候系统中存在着复杂的热量交换过程,包括太阳辐射、大气吸收和散射、海洋和陆地的热能储存与释放等。
这些过程的变化使得地球表面温度出现周期性变化。
其次,自然因素还包括大气环流系统的影响。
例如,季风系统、西风带等天气系统的运动会导致温度快速波动,并产生不同时间段内的温度异常。
此外,全球范围内发生的自然现象如厄尔尼诺-南方涛动(ENSO)和北极振荡也会对温度曲线产生明显影响。
2.2 人为因素人类活动也是导致温度曲线波动增大的重要原因之一。
工业活动、交通排放和森林砍伐等行为导致了大量二氧化碳等温室气体的排放,使得地球大气层中温室效应加强。
这进一步引发了全球变暖现象,导致温度在长期尺度上呈上升趋势,并加剧了温度曲线的波动。
此外,城市化和土地利用变化也会对局部气候产生显著影响。
例如,城市中的高楼大厦和混凝土地面可以吸收和储存大量热能,使得城市内部温度较农村地区更高,并引发城市热岛效应。
这种人为因素使得某些地区的温度曲线波动更加明显。
温度曲线的原理和应用1. 原理温度曲线是用来描述物质在不同温度下的性质变化情况的曲线图。
在物质的性质变化过程中,温度是一个非常重要的参量。
通过绘制温度曲线,我们可以了解物质在不同温度下的相变、化学反应等过程。
温度曲线的绘制原理主要根据温度的测量和数据记录。
通常,我们使用温度传感器来测量物体的温度,并将测得的温度数据记录下来。
然后,通过将温度数据绘制在坐标系内,就可以得到温度曲线。
2. 应用温度曲线在科学研究和工程应用中有广泛的应用。
下面列举几个常见的应用:•材料研究:温度曲线可以用于研究材料的热膨胀性质、相变温度、热导率等特性。
通过绘制材料在不同温度下的温度曲线,可以了解材料的热稳定性和热传导性能。
•食品加热研究:在食品加热过程中,通过绘制食品的温度曲线,可以了解食品在加热过程中的温度分布情况,从而了解食品的热传导性能和加热均匀性。
这对于食品的加热工艺优化和食品安全有重要意义。
•医学诊断:温度曲线可以用于医学诊断中的体温监测。
通过绘制体温的温度曲线,可以了解患者的体温变化情况,帮助医生判断患者是否发热或降温效果。
•环境监测:温度曲线可以用于环境监测中的温度监测。
通过绘制环境的温度曲线,可以了解环境的温度变化情况,帮助科学家研究地球气候变化和进行环境保护工作。
3. 绘制温度曲线的步骤绘制温度曲线通常需要以下步骤:1.温度测量:首先需要选择合适的温度传感器,如温度计、红外线温度计等,对待测物体进行温度测量。
确保测量准确性和稳定性。
2.数据记录:将测得的温度数据记录下来,包括时间和对应的温度数值。
可以使用数据记录仪、计算机等设备进行数据的实时记录和储存。
3.数据处理:将记录下来的温度数据进行处理,包括数据的清洗、筛选和处理。
根据需要,还可以进行数据的平滑处理、插值处理等。
4.绘制坐标系:根据温度数据确定坐标系的范围,并在纸上或电脑上绘制坐标系。
5.绘制温度曲线:根据处理后的温度数据,将点依次连接起来,即可得到温度曲线。
体感温度曲线根据不同情况有不同类型,具体如下:
正常排卵,低温期与高温期明显。
曲线效果:月经周期28天,基础体温曲线呈现标准的高低两相变化。
从月经开始到排卵日,持续低温期14天;排卵后持续高温14天,其中第14天为排卵日。
已怀孕,持续高温。
曲线效果:高温持续超过半个周期(16天)。
无排卵,持续低温。
曲线效果:持续低温(36.0℃-36.4℃),没有高温期,没有形成高低温双相变化。
黄体功能不良,体温缓慢下降。
曲线效果:排卵前是基础体温的低温期,排卵之后的半个月经周期是高温期,但是在高温期末尾,体温开始缓慢下降,而不是直接地急剧下降到低温段。
早期流产,持续高温后体温下降。
曲线效果:持续高温20天后体温下降。
人体一天温度变化曲线
人体的温度是一个非常复杂的系统,受到许多因素的影响。
一天中,人体的温度会随着时间的推移而发生变化。
下面是一个典型的人体一天温度变化曲线:
早上6点:人体温度最低。
这是因为身体在休息时,代谢率较慢,体温会下降到最低点。
早上8点:人体温度开始升高。
这是身体开始活动,代谢率加快,体温也随之升高。
中午12点:人体温度达到最高点。
这是因为人体在午餐时间之前已经进行了多次活动,并且消耗了大量的能量,因此体温达到最高值。
下午4点:人体温度开始下降。
这是因为人体进入下午的工作状态,代谢率开始减慢,体温也随之下降。
晚上8点:人体温度再次下降。
这是因为身体准备休息,代谢率减慢,体温也随之降低。
晚上10点:人体温度最低点。
这是因为身体在休息时,代谢率最低,体温也会降到最低点。
以上是人体一天温度变化的大致情况。
当然,每个人的情况都不同,因此人体温度变化曲线也可能会有所不同。
- 1 -。
人体温度曲线
人体体温一天变化曲线
正常成年人体温是36-37℃,一天当中人的体温是变化的,清晨2-6点体温最低,下午2-8点体温最高,一天之内体温的波动范围不超过1℃。
人的体温随年龄、性别、情绪等诸多因素,会出现正常的波动。
新生儿体温调节功能不完善,体温容易受环境温度的影响。
儿童代谢率增高,体温可以高于成年人,老年人由于基础代谢率低,体温可以在正常范围的低值,女性体温较男性稍高。
运动、洗热水澡、进食、精神紧张等因素,可以使体温一过性升高,而安静休息、饥饿或者服用镇静药以后可以使体温下降。
模量-温度曲线
热膨胀模量-温度曲线是研究物质受温度变化时它的体积变化关系的曲线,它
反映了物质的温度膨胀和热膨胀性能。
当物质在不同温度条件下改变体积时,其热膨胀模量-温度曲线会显示不同形状。
下面介绍四种不同类型的热膨胀模量-温度曲线类型。
第一种是线性热膨胀模量-温度曲线。
这一类的曲线的特征是,无论是温度的
变化程度,还是膨胀模量的变化程度,都是线性的。
这说明在低温和高温时,相应的物质改变体积的热膨胀模量的值的变化程度是一致的。
第二种是温度校正的热膨胀模量-温度曲线。
该类曲线显示了温度变化对膨胀
模量的影响。
这类曲线中,低温和中温下会出现不同程度的偏差,但高温时,膨胀模量会出现一定程度的减少。
第三种是温度补偿的热膨胀模量-温度曲线。
该类曲线和温度校正的热膨胀模
量-温度曲线不同,在覆盖温度范围在荷载条件下,其膨胀模量变化程度保持一致。
最后一种是多段式热膨胀模量-温度曲线。
该类曲线中,膨胀模量在分段的温
度区域内表现不同,具有多个温度变化期,在不同温度区段内,膨胀模量表现不同,例如它可以选择先减小,然后增大,再减小等多种变化形式。
此外,根据物质的构造本身,热膨胀模量-温度曲线也可以分为纯物料、混合物料和复合物料等几大类,本质也是前面几种曲线的一种特殊类型。
以上是热膨胀模量-温度曲线的简要介绍,不同类型的曲线可以反映不同的物
质温度膨胀和热膨胀性能,用于研究物质受温度变化时其体积变化关系。
此外,还可以用来评价材料在不同温度下的膨胀特性,便于更好地分析和利用物质所具有的材料性能。
温差降温曲线
温差降温曲线通常指的是温度随时间的变化曲线,在大气科学和气象学中,这种曲线可以描述一天内或某一段时间内温度的变化趋势。
在一天内,温差降温曲线一般呈现出以下特征:
1. 日出前后:温度处于最低点,即清晨时分。
2. 日间升温:随着太阳升起和日照的增加,温度开始上升,达到一天中的最高点。
3. 傍晚降温:太阳落山后,温度逐渐下降。
4. 夜间最低温:温度再次降至一天中的最低点,通常出现在深夜或凌晨。
这种曲线随着季节、地理位置和天气状况的不同会有所变化。
在不同季节或气候条件下,这种曲线的幅度和变化速度也会有所不同。
例如,夏季的温差降温曲线可能会相对平稳,而冬季则可能呈现出更大的幅度差异。
这种曲线对气象学、农业和生活等领域都有一定的应用,可以帮助人们更好地了解温度变化规律,为生产、生活和活动提供参考。
温度循环曲线是描述温度随时间变化的曲线图,通常用于测试和评估产品或材料在不同温度条件下的性能和耐久性。
它可以反映产品或材料在温度变化的环境下的可靠性和可持续性。
温度循环曲线通常由以下几个主要部分组成:
1.加热阶段(温度上升阶段):温度逐渐升高,产品或材料处于高温环境中。
此阶段可以用来模拟产品在高温环境下的使用情况或测试其热稳定性。
2.保持阶段(高温保持阶段):温度保持在一个稳定的高温值,使产品或材料长时间暴露在高温环境中。
这个阶段可以用来测试产品或材料的耐高温性能和长期使用下的稳定性。
3.冷却阶段(温度下降阶段):温度逐渐降低,产品或材料从高温环境中恢复到常温。
这个阶段可以用来测试产品或材料的低温适应性和冷却过程中的热膨胀与收缩等性能。
4.保持阶段(低温保持阶段):温度保持在一个稳定的低温值,使产品或材料长时间暴露在低温环境中。
这个阶段可以用来测试产品或材料的耐低温性能和低温下的稳定性。
温度循环曲线的具体形状和参数可以根据不同的测试要求和标准进行调整和设定,以模拟实际使用条件或特定的环境场景。
通过对温度循环曲线进行测试和分析,可以评估产品或材料在温度变化环境下的性能表现,为产品设计和材料选择提供依据,提高产品的质量和可靠性。
Modeling of simultaneous heat and mass transfer during convective oven ring cake bakingMelike Sakin-Yilmazer a ,⇑,Figen Kaymak-Ertekin a ,Coskan Ilicali ba Ege University,Faculty of Engineering,Department of Food Engineering,35100Bornova,Izmir,TurkeybKyrgyzstan-Turkey Manas University,Faculty of Engineering,Department of Food Engineering,720044Bishkek,Kyrgyzstana r t i c l e i n f o Article history:Received 11November 2011Received in revised form 2February 2012Accepted 11February 2012Available online 20February 2012Keywords:Ring cakeBaking modeling SimulationFinite difference method Heat and mass transfera b s t r a c tThe convective oven ring cake baking process was investigated experimentally and numerically as a simultaneous heat and mass transfer process.The mathematical model described previously by the authors for cup cake baking was modified to simulate ring cake baking.The heat and mass transfer mech-anisms were defined by Fourier’s and Fick’s second laws,respectively.The implicit alternating direction finite difference technique was used for the numerical solution of the representative model.Prior to the utilization of the developed model in predicting the temperature and moisture profiles for ring cake bak-ing,the results of the numerical model were compared with analytical results involving only heat or mass transfer with constant thermo-physical properties.Excellent agreement was observed.The numerical temperature and moisture contents predicted by the model were compared with the experimental pro-files.They agreed generally reasonably well with the experimental temperature and moisture profiles.Ó2012Elsevier Ltd.All rights reserved.1.IntroductionBaking is a complex process since the physical,chemical and biochemical changes taking place are of complex nature and these changes are simultaneous and coupled.Quantitative understand-ing of processes like volume expansion,evaporation of water,for-mation of a porous structure,denaturation of protein,gelatinization of starch,crust formation and browning reaction are still limited (Sablani et al.,1998;Zhang and Datta,2006).Sim-plified models for the baking process can be developed by treating baking as simultaneous heat and moisture transfer.Even for such simplified models,the estimation of the thermo-physical and transport properties,and the transfer coefficients is a challenging task.Nevertheless,mathematical models supply valuable informa-tion on baking process which may be utilized to optimize the bak-ing conditions to reduce energy consumption.As a traditional process,optimization and process control to ob-tain the desired final product quality is still largely based on expe-rience and good craftsmanship rather than on predictive calculations (Feyissa et al.,2011).Experimental and theoretical studies for baking in general and cake baking in particular were gi-ven in details in Sakin (2005)and Sakin et al.(2007b)and will not be repeated here.Mathematical models representing the baking process reduce the need for the tedious trial and error baking experiments to achieve a high quality product and they serve as a quick and prac-tical tool for pre-design,optimization and process control (Sakin et al.,2007b ).Ring cake is a popular cake geometry all over the world.Selecting this geometry as the test geometry and developing accurate mathematical models will have practical implications to-wards optimizing the baking conditions for better quality and en-ergy saving.Since there is no published work in literature about ring cake baking and its modeling,a two dimensional simplified mathemat-ical model for simultaneous heat and moisture transfer will be developed.Volume rise during baking will be considered.The pre-dictions of the numerical model will be compared with experimen-tal temperature and moisture content profiles.2.Material and experimentalThe cake batter was prepared by thoroughly mixing of 49.4%(of total weight)ready to bake dry cake mix (Dr.Oetker,containing wheat flour,sugar,corn starch,and baking powder),24.7%pasteur-ized whole liquid egg,16.2%vegetable margarine and 9.7%water.Its preparation was given in details in Sakin et al.(2007b).The ini-tial moisture content of the batter was %0.50kg water/kg dry solid.Teflon coated Aluminum was chosen as the material for ring cake mould due to Aluminum’s high thermal conductivity value (206W/mK,Geankoplis,2003).The ring baking mould was an annular ring having an annular radius of 0.04m,radius of 0.11and a height of 0.05m.Baking experiments were carried out in an electrical baking oven (Teba High-01Inox)which was0260-8774/$-see front matter Ó2012Elsevier Ltd.All rights reserved.doi:10.1016/j.jfoodeng.2012.02.020⇑Corresponding author.Tel.:+902323113039;fax:+902323427592.E-mail addresses:melike.sakin@.tr (M.Sakin-Yilmazer),figen.ertekin@.tr (F.Kaymak-Ertekin),coskan.ilicali@ (C.Ilicali).0.39Â0.44Â0.35m(LÂWÂH)wide.The batter was baked at three different oven temperatures(165,185and205°C)under forced convection conditions.The oven was preheated before the baking experiment to obtain uniform oven baking conditions.The air was circulated by a fan in-stalled on the back side of the oven at a constant speed(0.56m/s, measured by Airflow anemometer,LCA6000,UK)and fresh air en-tered steadily into the oven cavity,through a hole(/:28mm)up in the oven to prevent moisture accumulation.Moisture and temperature profiles were recorded during baking experiments.The procedures for taking temperature and moisture content data were similar to that given in Sakin et al.(2007b). Moisture profiles were measured at the top,bottom,annular and side surface crusts as two parallel measurements.An infrared moisture analyzer(Ohaus,MB200,USA),with a precision of ±0.007g,was used for the moisture content determination of the samples.The results obtained by the instrument were previously validated by the standard air oven method for total solids and moisture in baked products,as1h at130°C(AOAC,1995).Temperature profiles were recorded at the top(r=0.063m), bottom(r=0.08m)and annular(z=0.015m)surfaces by using j-type thermocouples(wire size,/:1mm;accuracy:1–1.5°C)that were calibrated in water and ice baths against glass mercury ther-mometer,and by a multi-channel data-logger(Hanna Inst.,HI 98804,Portugal)having an accuracy of±0.5°C,excluding probe er-ror.All the temperature measurements were conducted as two parallels.Techniques used in thermocouple positioning were sim-ilar to Sakin et al.(2007b).The change in the height of the cake batter was measured by a digital caliper(Mitutoyo,Digimatic,Japan).3.Mathematical model descriptionSimultaneous heat and moisture transfer mechanisms in a ring cake during baking can be described by the two dimensional(in r and z directions)unsteady state heat and moisture transfer equa-tions with appropriate boundary conditions.The Fourier’s equation for unsteady state heat conduction for solids with constant thermo-physical properties in afinite cylinder geometry can be modified by the addition of a phase change term to account for the evaporation of the product moisture(Sakin, 2005;Sakin et al.,2003,2004,2005,2007b;Tong and Lund, 1993;Thorvaldsson and Janestad,1999;Shilton et al.,2002).@T¼a1Á@Tþ@2Tþ@2T!þkPÁ@Xð1Þwhere,T is the temperature(°C),t is the time(s),a is the thermal diffusivity(a=k/q c P,m2/s),r is the distance in the radial direction (m),z is the distance in the upward direction(m),k is latent heat of vaporization of water(J/kg),c p is the specific heat capacity(J/kgK),X is the moisture content(kg water/kg dry solid),k is the thermal con-ductivity(W/mK)and q is the density(kg/m3).Uniform initial temperature distribution throughout the cake batter was assumed:t¼0;T¼T ini at all r and zð2Þwhere,T ini is the initial batter temperature(°C).The top,bottom,side and annular surfaces boundary conditions for heat transfer were written as Eqs.(3)–(6),respectively as shown below.kÁ@T@zr¼r;z¼H¼hÁT aÀT r;HðÞð3ÞÀkÁ@T@zr¼r;z¼0¼hÁT aÀT r;0ðÞð4ÞkÁ@T@rr¼R;z¼z¼hÁT aÀT R;zðÞð5ÞNomenclatureA(i),B(i),C(i),AA(i),BB(i),CC(i)elements of coefficient matrixBi Biot number for heat transfer,Bi r¼h cÂR=k;Bi z¼h cÂðH=2Þ=kBi m Biot number for moisture transfer,Bi mr¼k cÂRk cÂR=D eff;Bi mz k¼k cÂðH=2ÞD effc p specific heat(J/kgK)D eff effective moisture diffusivity(m2/s)D(i),DD(i)elements of the right-hand side vectorH thickness of cake batter(m)h surface heat transfer coefficient(W/m2K)k thermal conductivity(W/mK)k c convective mass transfer coefficient(m/s)M number of intervals in z directionMP1M+1,the top surface layerN number of intervals in r directionNH number of intervals in the cake in r directionNH1NH+1,annular surfaceNP1N+1,the radial axisr distance in radial direction(m)R the radius(m)T temperature(°C)T r oven surface temperature(°C)t time(s)U b lower surface overall heat transfer coefficient(W/m2K) U l lateral surface overall heat transfer coefficient(W/m2K) X moisture content(kg water/kg dry solid)z distance in upward direction(m) Subscriptsa ambientannulus annular surfaceb batterbottom bottom surfacecup baking cupdc donecakeeff effectiveffinali the i th nodeini initialj the j th noder,z the r and z directionssides side surfacetop top surfaceGreek symbolsa thermal diffusivity(m2/s)k latent heat of vaporization of water(J/kg) D r,D z the spatial increments in r and z directions.D x thickness(m)D t the time step(s)q the product density(kg/m3)290M.Sakin-Yilmazer et al./Journal of Food Engineering111(2012)289–298ÀkÁ@Tr¼R a;z¼z¼hÁT aÀT Ra;zðÞwhere,h is a convective and radiative surface cient(W/m2K),T a is the baking oven thickness of product(m),R is the radius of the R a is the annular radius(m).Fick’s2nd law describes the unsteady statein solids.Infinite cylinder geometry,the change tent with time and position during baking (Crank,1975).@X¼D eff 1Á@Xþ@2Xþ@2X!Initially a uniform moisture distribution waspositionst¼0;X¼X ini at all r and zwhere,X ini is the initial moisture content of cakedry solid).The experimental data obtained in thisthe moisture contents in the top,bottom,sidedropped sharply at the start of the baking process.Although the top surface moisture content was the lowest,the moisture con-tents for the bottom,side and annular crusts were of comparable values.As the cake batter expands in the upward direction,sharp decrease in the moisture contents and sharp increase in tempera-tures were observed in the layers of the batter in contact with the cake mould.When crust formation begins on the surfaces in contact with the mould surfaces,it is believed that the crust sepa-rates slightly from the hot Aluminum surfaces enabling the loss of moisture also from these surfaces.Therefore,to account for the moisture loss in surface layers effective mass transfer coefficients were assigned to these surfaces.The top surface moisture transfer boundary condition was defined as below,by Eq.(9).ÀD effÁ@X@zr¼r;z¼H¼k c;topÁX r;HÀX1ðÞð9Þwhere,k c,top is an effective convective mass transfer coefficient(m/ s),X1is the equilibrium moisture content in the oven medium.The bottom,side and annulus boundary conditions were de-fined similarly as follows by Eqs.(10)–(12),respectively.D effÁ@X@zr¼r;z¼0¼k c;bottomÁX r;0ÀX1ðÞð10ÞÀD effÁ@X@rr¼R;z¼z¼k c;sidesÁX R;zÀX1ðÞð11ÞD effÁ@Xr¼R a;z¼z¼k c;annulusÁX Ra;zÀX1ðÞð12Þ4.Numerical solution4.1.Grid systemThe cake batter in a ring shaped baking mould was a ring of ra-dius R,annular radius R a and height H.A schematic diagram of the coordinate system used is given in Fig.1.Any rectangular cross-section from the annular surface represents the whole product.A grid system where terms i and j were used to index the nodes in r and z directions was formed(Sakin(2005)).D r and D z were spa-tial increments,and N and M were numbers of intervals in the r and z directions.M was taken as20and N was taken as44.The number of intervals within the cake in the radial direction NH was taken as 28.The volume increase and the subsequent decrease during bak-ing were taken into account as linear changes in height.In the numerical solution,the height of the baking product was refreshed at each time step by using the regression equations obtained from experimental height versus time data.4.2.Solution methodThe governing partial differential equations,defining heat and moisture transfer have been approximated byfinite differences. The implicit alternating direction method was used for the solu-tion.The tri-diagonal matrix systems were formed and solved by the Gaussian Elimination method for the temperature profile,T i,j and moisture profile,X i,j at all points from i=1to NH+1,j=1to M+1,with a time step(D t)of2s(Carnahan et al.,1969;Chandra and Singh,1995).The elements of the coefficients matrix and the right-hand side vector in tri-diagonal matrix system were defined as A(i,j),B(i,j), C(i,j)and D(i,j)for heat transfer;AA(i,j),BB(i,j),CC(i,j)and DD(i,j) for moisture transfer,respectively by Sakin(2005).These coeffi-cients were modified for ring cake baking.The simulation of the model has been done by a computer pro-gram written on Fortran95.Theflow schema of the program is similar to the one given in(Sakin et al.,2007b).4.3.Verification of numerical method against analytical solutions for simplified geometries and materialsThe mathematical model developed for ring cake baking and its numerical results for temperature and concentration profiles must be verified against well known analytical solutions before ring cake baking simulation.The solution of the given coupled partial differ-ential equations,defining the simultaneous heat and mass transfer case of baking,by analytical methods is essentially impossible (Franks,1972).Therefore,the developed model was compared with possible analytical solutions and independently for heat and mass transfer.For heat transfer verification Eq.(1)without the phase change term was used.To eliminate the effect of mass trans-fer,all the mass transfer coefficients were taken as zero.To trans-form the ring cake to an infinite slab,the height of the cake was taken to be much smaller than the radius.When this is the case,M.the ring cake becomes an infinite slab with thickness being equal to the height of the ring cake.Predictions of the numerical model were compared with analytical solutions (Cengel,2003)for a wide range of Biot numbers.Excellent agreement was observed.To the knowledge of the authors,no analytical solution exists for unstea-dy state heat conduction in an annulus,with convective boundary conditions.Therefore,for radial testing of the model,the height of the ring cake was taken to be much larger than the radius and the number of radial intervals in the ring cake,NH,was taken to be equal to the total number of intervals À1,N À1.Furthermore,the heat transfer coefficient for the annular surface was taken to be zero (adiabatic axis).Under these conditions,the resulting geome-try will closely simulate an infinite cylinder geometry.The predic-tions of the ring cake numerical model were compared with the analytical solutions for infinite cylinder.A very high level of agree-ment between analytical and numerical models was obtained.A fi-nal check for the heat transfer section was performed by comparing the predictions of the numerical model with analytical solutions for a finite cylinder.The method of superposition was used for the analytical solution of the two dimensional partial dif-ferential equations.Input data used in the verifications for a finite cylinder are given in Table parison of the predictions of the numerical model for the center temperature with analytical solu-tions for a finite cylinder at Bi r =Bi z =1and Bi r =Bi z =10are shown in Fig.2.Excellent agreements were observed.For mass transfer verifications of the model,different cases were considered:In all these cases,the ambient temperature was as-sumed to be equal to the initial temperature and the latent heat was taken to be zero to eliminate heat transfer effects.Initially,the radius of the cake was taken to be much larger than the height and only convective mass transfer on the top surface was consid-ered.Under these conditions,the ring cake becomes an infinite slabwith half thickness being equal to the height of cake.For the second case used in mass transfer verifications,the radius of the cake was taken to be much larger than the height and convective mass trans-fer was considered for the top and bottom surfaces.The same mass transfer coefficients were used for the both surfaces.For this case,the ring cake becomes an infinite slab with thickness equal to height of the cake.Numerical predictions for the surface,symmetry axis and average moisture content were compared with the analyt-ical solutions for a wide range of mass transfer Biot numbers (Bi m ).Very good agreements were observed for all cases.For radial testing of the model,the height of the ring cake was taken to be much lar-ger than the radius and the number of radial intervals in the ring cake,NH,was taken to be equal to the total number of intervals À1,N À1,similar to the heat transfer case.Furthermore,the mass transfer coefficient for the annular surface was taken to be zero.Un-der these conditions,the resulting geometry will closely simulate an infinite cylinder geometry.Again,very good results were ob-tained for these cases for center,surface and average moisture con-tents.Final verification of the model for mass transfer was carried out for an impermeable hollow short cylinder where the annular ra-dius was 1/40times the cylindrical radius.This geometry is practi-cally a short cylinder.The input parameters used for mass transfer verifications are also given in Table 1.Constant transport properties and constant product thickness were parison of the predictions of the numerical model with analytical solutions for Bi mr =Bi mz =1and Bi mr =Bi mz =10for center and average moisture contents are shown in Figs.3and 4,respectively.The average moisture content was calculated by the following equation;X ave ¼2R 2ÀR 2aZRR aXrdr ð13ÞAs can be observed from Figs.2–4,the numerical model devel-oped predicts accurately the analytical temperature and moistureprofiles.The slight differences in the average moisture contents in Fig.4were attributed to numerical integration error in Eq.(13).Therefore,it was concluded that the numerical model devel-oped for ring cake baking can be used to simulate experimental temperature and moisture content profiles.4.4.Input parameters to ring cake baking simulation and method of validation of simulation resultsThe ring cake baking process parameters used during the numerical solution were the product dimensions,thermo-physicalTable 1Input parameters used in the verification of the numerical model.Cake dimensions (m)H :0.0462,R =0.0231Initial temperature,(°C)T ini =25.7Ambient temperature,(°C)T a =185Heat transfer coefficients (W/m 2K)h :10.39,103.9Thermal conductivity (W/mK)k :0.24Density (kg/m 3)q =945Specific heat capacity (J/kg K)Cp =2650Initial moisture content (kg water/kg dry solids)X ini =0.56Ambient moisture content (kg water/kg dry solids)X 1:0Mass transfer coefficient (m/s)k c =1.3Â10À5Effective diffusivity (m 2/s)D ef =3Â10À7,3Â10À8292M.Sakin-Yilmazer et al./Journal of Food Engineering 111(2012)289–298and mass transport properties,baking oven temperatures,the sur-face heat and mass transfer coefficients,the initial temperatureand moisture content of the cake batter which are illustrated by Table 2.They were either experimentally determined,estimated or taken from the literature to simulate the experimental ring cake baking process.The mass transfer coefficients for oven tempera-ture of 205°C were taken to be 20%higher than the corresponding values at 165and 185°C since the baking time to approximately the same final moisture content was 50min at 205°C,compared to 60min at 165and 185°C.The product density and thermal con-ductivity was assumed to change linearly with cake height accord-ing to the following equations:q ¼q b þðq dc Àq b ÞðH ÀH ini ÞðH f ÀH ini Þð14Þk ¼k b þðk dc Àk b ÞðH ÀH ini ÞðH f ÀH ini Þð15ÞThe specific heat capacity was also evaluated separately and then the thermal diffusivities were calculated.The cake height was measured experimentally.The change in cake height with time was represented by regression straight lines.The %absolute deviation (p ,%)between the experimental and numerical results,for temperature and moisture profiles,were cal-culated by Eq.(16)to validate the simulation results (Boquet,Chi-rife,Iglesias,1978).Table 2Baking process parameters and input variables.Ring cake dimensions (m)H a :0.025,R a a :0.04,R a :0.11Baking temperatures (o C)T a a :165,185,205Initial moisture content (kg moisture/kg solids)X ini a :0.543–0.567Initial temperature (o C)T ini a :23.7–25.7Batter density (kg/m 3)q b a :947.8Donecake density (kg/m 3)q dc a :320Batter thermal conductivity(W/mK)k b b :0.24k b b :0.24Donecake thermalconductivity(W/mK)k dc b :0.121Specific heat capacity (J/kg K)C p b :2650Heat transfer coefficients (W/m 2K)h a :16.3Mass transfer coefficients (m/s)k c ,top a ,c :2.40Â10À5,k c ,bottom a :1.68Â10À5,k c ,sides a :1.56Â10À5,k c ,annulus a :1.56Â10À5k c ,205a =1.2k c,165Effective moisture diffusivity (m 2/s)D eff a ,d :1.7Â10À8a Experimentally measured or estimated values.b Baik et al.(1999).c Demirkol et al.(2006).dSakin et al.(2007a).M.Sakin-Yilmazer et al./Journal of Food Engineering 111(2012)289–298293p ð%Þ¼100N ÁX Ni ¼1X exp ÀXnum j jX expð16Þ5.Results and DiscussionTemperature and moisture profiles at certain positions of thering cake during baking were determined.The difference between the experimental and numerical moisture profiles were compared by p%values;where,a value below 10%indicates the good fit be-tween both results (Boquet,Chirife,Iglesias,1978).The experimentally observed and numerically predicted tem-perature profiles at the positions of the product top surfaceaccuracy of the predictions.For this reason,the experimental data for the center temperature and model predictions were not re-ported in this research.Althoughmeasurements were performed at three oven temperatures,165,185and 205°C,only the results at 165and 205°C were shown to make the figures less crowded.The top surface numerical temperature profile predictions were in good agreement with the experimental results,especially to-wards the completion of baking period (Fig.5).The p %values were calculated as 6.5%and 3.8%,for 165and 205°C,respectively.The specification of the heat transfer coefficient is crucial in heat trans-fer calculations especially at small Biot numbers.When we have a ring cake,the characteristic dimension to be used in the Biot num-ber is ambigous,since we have an annular geometry and the height of the cake also changes.However,if we take (R –R a )is the charac-294M.Sakin-Yilmazer et al./Journal of Food Engineering 111(2012)289–298h¼_mWkAðT aÀTÞtð17Þwhere_m W is the total moisture evaporated(kg)during a com-plete baking run,A is the total heat transfer area(m2),T is the sur-face temperature(o C)and t is the baking time(s);3600s for165°C and3000s for205°C.The surface temperature was assumed to be the mean of ambient temperature and100°C.A single heat trans-fer coefficient was used in all runs.Radiative contribution to heat transfer was not considered.Sakin et al.(2009)have shown that the oven wall temperature and the oven medium temperature dif-fer appreciably depending on oven medium temperature.For an oven medium temperature of160°C,the oven wall average tem-perature was181.6°C in the forced convection oven.At higher oven temperatures,the wall and medium temperature approaches to each other.In the present work,lack of experimental data on heat transfer coefficients will lead to inaccuracies in temperature predictions.The predicted bottom temperatures(Fig.6)were in good agree-ment with the experimental temperatures especially at an oven medium temperature of205°C.The p%values were calculated as 6.1%and3.9%,for165and205°C,respectively.The same heat transfer coefficient was used for all surfaces.However,the convec-tive and radiative heat transfer coefficients will be different for dif-ferent surfaces.Accurate determination of the heat transfer coefficients will be essential for more accurate predictions.Annular surface temperature predictions by the present model were com-pared with experimental values in Fig.7.Satisfactory agreement was observed for oven medium temperature of165°C,where the p%value was calculated as5.5%.However,experimental tempera-tures were greater than the predicted temperatures for205°C.The p%value was calculated as10.9%.This larger deviation was again attributed to the use of the same heat transfer coefficient for all surfaces.The estimation of thermo-physical properties of the ring cake and the transfer coefficients were very important in the numerical solution.They were mostly taken from the related liter-ature(Table2).The differences between the experimental temper-ature profiles and the numerical predictions can also be attributed to these inaccuracies in the thermo-physical properties.More com-prehensive studies on the thermo-physical property estimation of a baking cake batter and the estimation of heat transfer coefficients at different surfaces on a ring cake will result in more accurate numerical models.Similarly,the effective moisture diffusivity term and the mass transfer coefficients have a strong effect on the moisture profile prediction.The relative importance of the estimation of these two parameters will depend on the mass transfer Biot number.It may be shown from the data in Table2that mass transfer Biot numbers vary between11and66.For mass transfer,the internal resistance controls the diffusion of moisture.Therefore,accurate estimation of the effective diffusivity is essential for accurate mass transfer modeling.The available literature for this property for cake baking was limited mostly to the model equations generated for a thin layer of cake batter during drying/baking(Baik and Marcotte,2002;Sakin et al.,2005,2007a)and cup cake baking (Sakin et al.,2007b).As pointed out by Sakin et al.(2007b)the use of the proposed effective moisture diffusivity expressions by Baik and Marcotte(2002)and Sakin(2005)resulted in higher moisture profiles than experimental results.Although the effective diffusivity does not depend on the system geometry,for the same material,the geometry chosen in the estimation of the diffusivity affects the diffusion behaviour.Thus,the effective diffusivities cal-culated from experimental moisture data obtained from the drying or baking of a model system,will be indirectly affected by the geometry,in this case the ring cake.Rather than modifying these expressions,a constant effective diffusivity value was used for the sake of simplicity.The effective moisture diffusivity was taken as1.7Â10À8m2/s in line with the observations of Sakin(2005).When the moisture contents of different crusts of the ring cake were examined,it was observed that generally the top crust had the lowest moisture content and the bottom crust had the second lowest moisture.Moisture profiles for the side and annular crusts were higher than the top and bottom moisture contents and were very similar.Considering the moisture profiles,the top surface con-vective mass transfer coefficient was taken as 1.3Â10À5m/s (Demirkol et al.,2006).The effective convective mass transfer coef-ficients for the other surfaces were taken as shown in Table2.The experimentally observed and numerically predicted moisture pro-files at the top,bottom,side and annular surface positions for oven temperatures of165and205°C were shown in Figs.8–11.In almost all cases,thefinal numerical moisture contents were in close agreement with the experimental values.For the top crust moisture content(Fig.8)the numerical and experimental moisture profiles agreed quite well at165°C(p%value is9.1%).For oven temperature of205°C,the experimental profiles were lower than the numerical profiles;with a p%value larger than10%,indicating that the temperature dependence of the mass transfer coefficient and the effective diffusivity should be considered for this surface. For the bottom surface(Fig.9),the experimental and numerical moisture profiles agreed very well at205°C with a p%8.2.How-ever,at165°C,experimental profiles were higher than the numer-ical ones(the p%value equals to10.0).This can again beattributed M.Sakin-Yilmazer et al./Journal of Food Engineering111(2012)289–298295。