Hybrid versus global thermostatting in molecular-dynamics simulation of methane-hydrate crystallisation

Molecular-dynamics(MD)simulations have been performed for the growth of a spherical methane-hydrate nano-crystallite,surrounded by a supersaturated water–methane liquid phase,using both a hybrid and globalsystem thermostatting approach.It was found that hybrid thermostatting led to more sluggish growth and the establishment of a radial temperature profile about the spherical hydrate crystallite,in which the growing crystal phase is at a higher temperature than the surrounding liquid phase in the interfacial region,owing to latent-heat dissipation.In addition,Onsager’s-hypothesis fluctuation–dissipation analysis of fluctuations in the number of crystal-state water molecules at the interface shows slower growth.

Numerical distortion and effects of thermostat in molecular dynamics simulations of single-walled carbon nanotubes

In this paper, single-walled carbon nanotubes （SWCNTs） are studied through molecular dynamics （MD） simulation. The simulations are performed at temperatures of 1 and 300K separately, with atomic interactions characterized by the second Reactive Empirical Bond Order （REBO） potential, and temperature controlled by a certain thermostat, i.e. by separately using the velocity scaling, the Berendsen scheme, the Nose-Hoover scheme, and the generalized Langevin scheme. Results for a （5,5） SWCNT with a length of 24.5 nm show apparent distortions in nanotube configuration, which can further enter into periodic vibrations, except in simulations using the generalized Langevin thermostat, which is ascribed to periodic boundary conditions used in simulation. The periodic boundary conditions may implicitly be applied in the form of an inconsistent constraint along the axis of the nanotube. The combination of the inconsistent constraint with the cumulative errors in calculation causes the distortions of nanotubes. When the generalized Langevin thermostat is applied, inconsistently distributed errors are dispersed by the random forces, and so the distortions and vibrations disappear. This speculation is confirmed by simulation in the case without periodic boundary conditions, where no apparent distortion and vibration occur. It is also revealed that numerically induced distortions and vibrations occur only in simulation of nanotubes with a small diameter and a large length-to-diameter ratio. When MD simulation is applied to a system with a particular geometry, attention should be paid to avoiding the numerical distortion and the result infidelity.

Extensive Numerical Tests of Leapfrog Integrator in Middle Thermostat Scheme in Molecular Simulations

Accurate and efficient integration of the equations of motion is indispensable for molecular dynamics(MD)simulations.Despite the massive use of the conventional leapfrog(LF)integrator in modern computational tools within the framework of MD propagation,further development for better performance is still possible.The alternative version of LF in the middle thermostat scheme(LFmiddle)achieves a higher order of accuracy and efficiency and maintains stable dynamics even with the integration time stepsize extended by several folds.In this work,we perform a benchmark test of the two integrators(LF and LF-middle)in extensive conventional and enhanced sampling simulations,aiming at quantifying the time-stepsizeinduced variations of global properties(e.g.,detailed potential energy terms)as well as of local observables(e.g.,free energy changes or bondlengths)in practical simulations of complex systems.The test set is composed of six chemically and biologically relevant systems,including the conformational change of dihedral flipping in the N-methylacetamide and an AT(AdenineThymine)tract,the intra-molecular proton transfer inside malonaldehyde,the binding free energy calculations of benzene and phenol targeting T4 lysozyme L99A,the hydroxyl bond variations in ethaline deep eutectic solvent,and the potential energy of the blue-light using flavin photoreceptor.It is observed that the time-step-induced error is smaller for the LFmiddle scheme.The outperformance of LF-middle over the conventional LF integrator is much more significant for global properties than local observables.Overall,the current work demonstrates that the LF-middle scheme should be preferably applied to obtain accurate thermodynamics in the simulation of practical chemical and biological systems.

Design and Development of New Digital Thermostat

The designed thermostat is based on the microcontroller featuring intelligence, programmable, environmental protection and power saving. The thermostat design is mainly composed of hardware and software design, the hardware includes the power supply circuit, temperature measurement circuit, humidity measurement circuit and backlight circuit; while the software design includes temperature measurement and compensation algorithm, moreover software flowchart is given as well. Finally the power supply circuit is simulated by the software of Pspice and the creative power stealing mode is verified by the simulation results. A target board is stuffed by hand with Pb-free electronic components and used to test hardware and debug software. Since the Pb-free components were used, power stealing mode is designed in hardware and temperature compensation algorithm is accomplished in software, and the thermostat is outstanding with its features of "green" and "power saving".

Deep Unity of Classic and Quantum Physics at the Space Thermostat Presence with Technical Applications

The paper demonstrates deep unity of classic and quantum physics at the space thermostat (ST) presence, which fulfilled all space by the temperature T0 = 2.73 K. The ST presents itself the Cosmic Microwave Background (CMB). From the main quantum position we consider the ST/CMB as the wave function carrier (“quantum background”). The paper is devoted to ST/CMB medium the classic conservation laws of mass, momentum and energy. We show the soliton like solutions of our classic model correspond to Schrodinger’s quantum solutions, demonstrate the atom hydrogen specter and other quantum peculiarities. The paper contains typical technical examples classic/ quantum simulation at the ST presence.

Numerical Heat Transfer Modelling for Rapid Impact Assessment of Limiting Thermostat Reliability on Fuel-Oil Burner Pre-Heaters： A Case Study

In this paper, the impact of limiting thermostat on the rupture event occuring in Fuel-Oil burner fuel pre-heaters＇ resistant （heat generating） wires is inspected numerically. Gaseous fuel content in the pipeline has also been issued as a possibility. Heater＇s inner temperature distributions have been simulated by an in-house MATrix LABoratory （MATLAB） script in order to understand the resistant wire exposure to high temperatures by numerous scenarios. It is concluded that the effect of fuel flowrate is not a major effect on the wires＇ fate because of the limiting thermostat co-working. The main difference between the calculations is the effect of thermostat cut off function. The numerical simulations enlightened the dominant effect of thermostat sensing delay, so the overheating event. Intolerable delay results with a quick drop in the thermal efficiency and an increased possibility on wire rupture due to overheating which means a burner malfunction. Referring to the first numerical simulation results, a distributed and reduced heat flux was implemented with the same fluid and thermodynamic properties on a revised pre-heater model with an increased heater plate. The increment, thus the reduction on the heat flux of the ribbon wires has been noted as the key for safe operation.

A reinforcement learning approach for thermostat setpoint preference learning

Occupant-centric controls(OcC)is an indoor climate control approach whereby occupant feedback is used in the sequence of operation of building energy systems.While OcC has been used in a wide range of building applications,an OcC category that has received considerable research interest is learning occupants'thermal preferences through their thermostat interactions and adapting temperature setpoints accordingly.Many recent studies used reinforcement learning(RL)as an agent for OcC to optimize energy use and occupant comfort.These studies depended on predicted mean vote(PMV)models or constant comfort ranges to represent comfort,while only few of them used thermostat interactions.This paper addresses this gap by introducing a new off-policy reinforcement learning(RL)algorithm that imitates the occupant behaviour by utilizing unsolicited occupant thermostat overrides.The algorithm is tested with a number of synthetically generated occupant behaviour models implemented via the Python APl of EnergyPlus.The simulation results indicate that the RL algorithm could rapidly learn preferences for all tested occupant behaviour scenarios with minimal exploration events.While substantial energy savings were observed with most occupant scenarios,the impact on the energy savings varied depending on occupants'preferences and thermostat use behaviour stochasticity.

Multifactor roadmap for designing low-power-consumed micro thermoelectric thermostats in a closed-loop integrated 5G optical module

As the core components of fifth-generation(5G)communication technology,optical modules should be consistently miniaturized in size while improving their level of integration.This inevitably leads to a dramatic spike in power consumption and a consequent increase in heat flow density when operating in a confined space.To ensure a successful start-up and operation of 5G optical modules,active cooling and precise temperature control via the Peltier effect in confined space is essential yet challenging.In this work,p-type Bi_(0.5)Sb_(1.5)Te_(3)and n-type Bi_(2)Te_(2.7)Se_(0.3)bulk thermoelectric(TE)materials are used,and a micro thermoelectric thermostat(micro-TET)(device size,2×9.3×1.1mm^(3);leg size,0.4×0.4×0.5mm^(3);number of legs,44)is successfully integrated into a 5G optical module with Quad Small Form Pluggable 28 interface.As a result,the internal temperature of this kind of optical module is always maintained at 45.7°C and the optical power is up to 7.4 dBm.Furthermore,a multifactor design roadmap is created based on a 3D numerical model using the ANSYS finite element method,taking into account the number of legs(N),leg width(W),leg length(L),filling atmosphere,electric contact resistance(Rec),thermal contact resistance(Rtc),ambient temperature(Ta),and the heat generated by the laser source(QL).It facilitates the integrated fabrication of micro-TET,and shows the way to enhance packaging and performance under different operating conditions.According to the roadmap,the micro-TET(2×9.3×1mm^(3),W=0.3 mm,L=0.4 mm,N=68 legs)is fabricated and consumes only 0.89W in cooling mode(Q_(L)=0.7W,T_(a)=80℃)and 0.36Win heating mode(T_(a)=0℃)to maintain the laser temperature of 50℃.This research will hopefully be applied to other microprocessors for precise temperature control and integrated manufacturing.

Three-stage day-ahead scheduling strategy for regional thermostatically controlled load aggregators

Thermostatically controlled loads(TCLs)are regarded as having potential to participate in power grid regulation.This paper proposes a scheduling strategy with three-stage optimization for regional aggregators jointly participating in day-ahead scheduling to support demand response.The first stage is on the profit of aggregators and peak load of the grid.The line loss and voltage deviation of regulation are considered to ensure stable operation of the power grid at the second stage,which guarantees the fairness of the regulation and the comfort of users.A single tempera-ture adjustment strategy is used to control TCLs to maximize the response potential in the third stage.Finally,digital simulation based on the IEEE 33-bus distribution network system proves that the proposed three-stage scheduling strategy can keep the voltage deviation within±5%in different situations.In addition,the Gini coefficient of distribu-tion increases by 20%and the predicted percentage of dissatisfied is 48%lower than those without distribution.

Lean and interpretable digital twins for building energy monitoring - A case study with smart thermostatic radiator valves and gas absorption heat pumps

The transition to low carbon energy systems poses challenges in terms of energy efficiency.In building refur-bishment projects,efficient technologies such as smart controls and heat pumps are increasingly being used as a substitute for conventional technologies with the aim of reducing carbon emissions and determining operational energy and cost savings,together with other benefits.Measured building performance,however,often reveals a significant gap between the predicted energy use(design stage)and actual energy use(operation stage).For this reason,lean and interpretable digital twins are needed for building energy monitoring aimed at persistence of savings and continuous performance improvement.In this research,interpretable regression models are built with data at multiple temporal resolutions(monthly,daily and hourly)and seamlessly integrated with the goal of verifying the performance improvements due to Smart thermostatic radiator valves(TRVs)and gas absorption heat pumps(GAHPs)as well as giving insights on the performance of the building as a whole.Further,as part of modelling research,time of week and temperature(TOWT)approach is reformulated and benchmarked against its original implementation.The case study chosen is Hale Court sheltered housing,located in the city of Portsmouth(UK).This building has been used for the field-testing of innovative technologies such as TRVs and GAHPs within the EU Horizon 2020 project THERMOSS.The results obtained are used to illustrate possible extensions of the use of energy signature modelling,highlighting implications for energy management and innovative building technologies development.

基于恒热流法和恒温法的岩土热物性试验分析研究

目前岩土热物性测试仪采用的方法包括两种:恒热流法和恒温法,通过介绍两种测试方法的区别及模型算法,以北京市某公建项目岩土热物性测试结果为基准,利用TRNSYS软件分别模拟了恒热流法和恒温法的测试工况,针对模拟结果展开分析研究。经对比,试验时间至48 h时,两种测试方法利用软件模拟出的延米换热量与现场测试结果的误差在10%以内,表明若已知项目周边的地层热物性参数如地层的导热系数、热扩散率等,可将软件模拟结果作为前期地埋管系统设计的依据,并作为后续热物性勘察结果验证的参考数据。此外,根据模拟结果,由于夏季地埋管流体在设计工况下与土壤的温差值较大,为了使流体尽快达到设计工况点,恒温法测试时应选用较大的功率,否则48 h内的测试值结果与实际值偏差较大。

基于长短时记忆网络的恒温水浴锅温度模型预测

【目的】由于恒温水浴锅温度系统存在强非线性及大滞后性,本研究提出一种基于长短时记忆网络的恒温水浴锅温度模型预测方法。【方法】首先,对采集到的数据进行标准化处理,寻找长短时记忆网络的最优结构及超参数,用来拟合出最佳的数据映射特征,并构建恒温水浴锅温度的动态数学模型。其次,通过模型对未来一段时间内的温度趋势进行预测。最后,使用本研究提出的方法与最小二乘法所预测的结果进行对比分析。【结果】本研究所提方法构建的模型的拟合度达到了98.2%,预测结果的MSE及MAE比最小二乘法模型分别降低了4.616、0.823。【结论】本研究所提方法具有更高的预测精度,对提高恒温水浴锅的生产效率及控制精度具有重要意义。

高效液相色谱法测定室温下硝酸甘油注射液的存贮期限

目的高效液相色谱法测定硝酸甘油注射液在室温下的含量变化,预测硝酸甘油注射液在室温下的存贮期限。方法(1)HPLC法测定硝酸甘油注射液的含量。采用色谱柱(Kromasil C18),以甲醇:水(59:41)为流动相,流速1.0 ml·min^(-1),检测波长215 nm,柱温30℃;(2)采用加速试验和长期留样试验对硝酸甘油注射液的稳定性进行研究,经典恒温试验预测其在室温下的有效期。结果硝酸甘油注射液检测浓度在10μg·ml^(-1)-600μg·ml^(-1)范围内与峰面积呈良好的线性关系(R=0.9999),日内精密度、日间精密度、稳定性试验、重复性实验RSD均小于2%,含量测定平均值在99.99μg·ml^(-1)(标准值100μg·ml^(-1)),加样回收率RSD为1.67%。经典恒温试验测得硝酸甘油的含量变化符合一级反应规律,在25℃,硝酸甘油注射液的速率变化常数K_(25)=7.1395×10^(-4),有效贮存期限为147 d;在30℃时,K_(30)=9.4175×10^(-4),有效贮存期限为111 d。长期留样观察实验可以验证该实验的可靠性。结论高效液相色谱法检测方法简单、快速、精密度高,重复性好。硝酸甘油注射液在室温(25℃)下的存储期限约5个月,可以为临床管理抢救车药品提供参考依据。

针对温控负载变化的虚拟电厂控制策略研究

温控负载是一种变化剧烈、波动频繁、高峰负荷比例较高的负载,对电网的安全产生了极大的影响。为了应对这一问题,系统的输出功率往往会超过90%负荷最大值的调峰限制。针对虚拟电厂(VPP)系统内的超限过程进行了研究,并提出了2种控制策略,以降低超限总电量或者利用超限电量的同时获取收益。在验证策略的控制效果时,选取了2种由温控负载引起的功率需求的典型变化。研究结果表明,温控负载引起的功率需求峰值的变化对策略具有重要影响。在安全模式下,超限比例与峰值的增加呈反比,而与平均功率的增加呈正比;在收益模式下,峰值变化会影响储能放电过程,平均功率变化则会影响储能充电过程。随着功率需求的增加,收益逐渐减小,收益范围为3.62万~3.25万元。

空调温控负荷集群参与光伏消纳的潜力评估与互动框架

空调温控负荷集群作为当下最具调节潜力的需求侧响应资源之一,在削峰、填谷、分布式光伏消纳和电网调控中将发挥重要作用。因此,提出一种电力市场环境下,基于数据驱动和深度置信网络的空调温控负荷集群参与分布式光伏消纳的可调节潜力评估与互动框架。首先,利用数据驱动构建了基于深度置信网络的可调节潜力评估模型,实时输出温控负荷集群的可调节潜力;其次,考虑功率调整量在一定范围内变化的前提下,构建基于深度置信网络的需求互动模型,对温控负荷集群进行实时温度调控。最后,以冀北地区某10kV馈线作为实际算例进行分析,结果表明:所提框架能够充分利用空调温控负荷集群的可调节潜力,参与分布式光伏的消纳。

不同恒温时间下疏浚砂砂浆力学及微观性能

为了对不同恒温时间下不同疏浚砂掺量砂浆的特性进行研究,选取恒温时间(4、8、12、16 h)、疏浚砂掺量(0%、15%、50%)为试验变量,利用长江下游疏浚砂替代机制砂制备了15组试件进行试验,根据试验结果分析了不同恒温时间对不同疏浚砂掺量砂浆抗压性能及微观结构的作用机理。结果表明:当疏浚砂掺量为0%和50%时,随着恒温时间增加,后期抗压强度先增大后减小,恒温时间为8 h时最大;当疏浚砂掺量为15%时,随着恒温时间增加,后期抗压强度逐渐减小,恒温时间为4 h时最大;恒温时间越长,蒸养损伤越大,不利于后期强度发展,不同疏浚砂掺量下变化规律不同;随着疏浚砂掺量增加,后期抗压强度先增大后减小,疏浚砂掺量为15%时最大;掺入疏浚砂对砂浆抗压强度有一定的优化作用,粒径极小的疏浚砂颗粒能有效填充砂浆中的孔隙缺陷,特别是经过蒸养损伤过后的砂浆,蒸养条件下疏浚砂的优化作用被放大,疏浚砂砂浆的抗压强度得到了进一步提升,疏浚砂对蒸养砂浆抗压强度的提升远大于标养砂浆,且恒温时间越长,抗压强度提升越明显;在恒温时间为4~8 h、疏浚砂掺量为15%的情况下,能制备出性能不低于纯机制砂砂浆的蒸养疏浚砂砂浆。

A day-ahead scheduling framework for thermostatically controlled loads with thermal inertia and thermal comfort model

This paper proposes a day-ahead dispatch framework of thermostatically controlled loads(TCLs) for system peak load reduction. The proposed day-ahead scheduling framework estimates the user’s indoor thermal comfort degree through the building thermal inertia modelling. Based on the thermal comfort estimation, a dayahead TCL scheduling model is formulated, which consists of 3 stages: TCL aggregator estimates maximal controllable TCL capacities at each scheduling time interval by solving a optimization model;[ the system operator performs the day-ahead system dispatch to determine the load shedding instruction for each aggregator;and ′the TCL aggregator schedules the ON/OFFcontrol actions of the TCL groups based on the instruction from the system operator. A heuristic based optimization method, history driven differential evolution(HDDE)algorithm, is employed to solve the day-ahead dispatch model of the TCL aggregator side. Simulations are conducted to validate the proposed model.

Day-ahead scheduling of large numbers of thermostatically controlled loads based on equivalent energy storage model

Due to their heat/cool storage characteristics, thermostatically controlled loads(TCLs) play an important role in demand response programmers. However, the modeling of the heat/cool storage characteristic of large numbers of TCLs is not simple. In this paper, the heat exchange power is adopted to calculate the power instead of the average power, and the relationship between the heat exchange power and energy storage is considered to develop an equivalent storage model, based on which the time-varying power constraints and the energy storage constraints are developed to establish the overall day-ahead schedulingmodel. Finally, the proposed scheduling method is verified using the simulation results of a six-bus system.

AZ31镁合金薄板热油恒温成形数值模拟与实验研究

利用有限元模拟和成形实验相结合的方式,研究AZ31镁合金的成形性能,基于Dynaform模拟软件和热油恒温成形设备,探究出一种适合镁合金的热成形工艺,并对成形件显微组织进行分析.研究表明,通过调整薄板尺寸、模具R角、压边力及摩擦系数等工艺参数,以降低成形件的底部减薄率,减少破裂倾向,提高镁合金的成形性能;成形温度为200℃,模具R角为16 mm,薄板直径为80 mm,并调整合适压边力和摩擦系数,可获得最佳的工艺窗口;靠近成形件底部,晶粒及第二相尺寸逐渐减小并趋于均匀化.

Experimental Analysis and Evaluation of Thermostat Effects on Engine Cooling System

Thermostat as a part of engine cooling system has a significant role in the shortening warm-up time and regulating the engine in proper temperature to approach optimal performance.Whereas,there is not adequate research on this part of the cooling system and its responsibility.Considering this gap and also being used in large scale,this study is intended to evaluate performance and reflex of the wax type thermostat in different engine working conditions.In this regard,performance of engine cooling system was investigated in various engine speeds and loads to reveal positive and negative influences of thermostat on engine cooling efficiency and engine performance.According to observed results,warm-up period and fuel consumption decrease by using a thermostat.On the other hand,however,the temperature oscillation of coolant fluid passing through engine increases sharply,which causes a disruption in the regulating engine temperature and also a possibility of the fluid boiling rises in some regions of the engine that increases the risk of damage in the engine parts.Engine temperature,fuel consumption,warm-up duration and emissions were provided and compared in two operation modes,with and without thermostat.