Peristaltic flow in an asymmetric channel with convective boundary conditions and Joule heating

The peristaltic transport of viscous fluid in an asymmetric channel is concentrated. The channel walls exhibit convective boundary conditions. Both cases of hydrodynamic and magnetohydrodynamic(MHD) fluids are considered. Mathematical analysis has been presented in a wave frame of reference. The resulting problems are non-dimensionalized. Long wavelength and low Reynolds number approximations are employed. Joule heating effect on the thermal equation is retained. Analytic solutions for stream function and temperature are constructed. Numerical integration is carried out for pressure rise per wavelength. Effects of influential flow parameters have been pointed out through graphs.

Influence of heat treatment conditions on bending characteristics of 6063 aluminum alloy sheets

Bending deformation behaviors of solution treated(ST),natural aged(NA)and T6tempered6063aluminum alloy sheetswere studied by three-point bending tests.The changes of bending force,interior angle,bending radius and sheet thickness in thefillet region were analyzed by experimental measurements and numerical simulations.The results showed that the bendingcharacteristics were strongly dependent on the heat treatment conditions.The T6alloy sheets were bent more sharply and localplastic deformation occurred severely in the fillet region.However,the ST and NA alloy sheets exhibited relatively uniform bendingdeformation and large bending radius.The bending force of T6alloy was the highest,followed by the NA alloy and that of the STalloy was minimum.After unloading,as compared with the ST and NA alloys,the springback of T6alloys was markedly larger.Theaging time showed a positive sensitivity on the springback and non-uniform bending deformability.The bending characteristics areattributed to the combined effects of yield strength,yield ratio and coefficient of neutral layer.

Role of Heating Condition in Polyethylene Behaviors under Nitrogen and Air Atmosphere

Recycle of plastic waste is an indisputable means to alleviate both environment and energy crisis.In this work,effects of heating condition on polyethylene behaviors in nitrogen and air were studied.It was observed that polyethylene behavior was a single step in nitrogen,while the multiple steps occurred in air.According to the weight loss and heat flow curves,polyethylene behaviors in air were divided into three regions:low-temperature(<340 ℃),middle-temperature(340 – 380 ℃) and high-temperature(> 380 ℃) regions.Kinetic analysis revealed that the partial oxidization took the dominance in the low-temperature region,which seldom formed CO and CO_(2);the combustion took the dominance in the middle-temperature region,which was positive to the formation of CO and CO_(2);the pyrolysis was initiated and enhanced in the high-temperature region,which inhibited the formation of CO and CO;.According to the kinetic simulation,a synergistic effect between the pyrolysis and combustion was proposed to account for the acceleration of polyethylene conversion.This work may provide useful information about polyethylene behaviors under heating condition,and help to design and optimize plastic waste incineration process.

Heat transfer in a porous saturated wavy channel with asymmetric convective boundary conditions

The viscous flow in a wavy channel with convective boundary conditions is investigated. The channel is filled with a porous viscous fluid. Two cases of equal and different external convection coefficients on the walls are taken into account. Effect of viscous dissipation is also considered. The governing equations are derived employing long wavelength and low Reynolds number approximations. Exact closed form solutions are obtained for the simplified equations. Important physical features for peristaltic flow caused by the wavy wave are pumping, trapping and heat transfer rate at the channel walls. These are discussed one by one in depth and detail through graphical illustrations. Special attention has been given to the effects of convective boundary conditions. The results show that for Bi1≠Bi2, there exists a critical value of Brinkman number Brc at which the temperatures of both the walls become equal. And, for Bi1>Bi2 and Br>Brc, the temperature of the cold wall exceeds the temperature of hot wall.

THE EXERGETIC EFFICIENCY OF MSF PROCESS AND THE CONDITIONS OF DESALINATION BY WASTE HEAT

The exergy losses and thermodynamic efficiency of MSF plant with brine recirculation are discussed bymeans of temperature difference functions proposed by the auther.In a MSF plant,the irreversible losses are found mainly in irreversible heat-transfer and flash evaporationprocesses.However,the basic variables are the temperature drop from stage to stage and the temperaturedifferences between flashed vapor and cooling water.In this paper,the flash temperature difference func-tion,the heat transfer temperature difference function and the total temperature difference function are sug-gested.The proposed temperature difference functions of MSF plant provide a convenient tool to analyse theirreversible behavior and evaluate the exergetic efficiency of this system,because without such improvement thecalculation of the exergetic efficiency of a MSF plant according to the classical formula will be not onlyinconvenient but also insignificant.As a result of present analysis,the reasonable parameters based on theenergy consumption are easily chosen.The above-mentioned principles are confirmed by commercial plants and a pilot plant in Tianjin.

Practice and analysis of recycling non-drinking water from air-condition and reverse-osmosis system into rainwater collection system

This paper is based on the rainwater collection project in the retrofit of the Dongyi teaching block in Zhejiang University Xixi Campus.The analysis incorporates the local meteorological data, recycling water utilization, and precipitation adjustment.The rainwater collection system in this program also adds the condensation water from the heating, ventilation and air conditioning （ HVAC） system and the concentration from the reverse-osmosis system used for watering greens and supplying waterscapes.By calculating, the quantity of the HVAC condensation water in summer is 3.48 m3/d, and the quantity of the reverse-osmosis concentrated water is 198 to 396 L/d.This method solves the water shortage caused by high evaporation in summer and low precipitation in winter.Supported by empirical monitoring data, the proposed method significantly increases the economic efficiency of the system during the summer period.

Country-level meteorological parameters for building energy efficiency in China

Accurate basic data are necessary to support performance-based design for achieving carbon peak and carbon neutral targets in the building sector.Meteorological parameters are the prerequisites of building thermal engineering design,heating ventilation and air conditioning design,and energy consumption simulations.Focusing on the key issues such as low spatial coverage and the lack of daily or higher time resolution data,daily and hourly models of the surface meteorological data and solar radiation were established and evaluated.Surface meteorological data and solar radiation data were generated for 1019 cities and towns in China from 1988 to 2017.The data were carefully compared,and the accuracy was proved to be high.All the meteorological parameters can be assessed in the building sector via a sharing platform.Then,country-level meteorological parameters were developed for energy-efficient building assessment in China,based on actual meteorological data in the present study.This set of meteorological parameters may facilitate engineering applications as well as allowing the updating and expansion of relevant building energy efficiency standards.The study was supported by the National Science and Technology Major Project of China during the 13th Five-Year Plan Period,named Fundamental parameters on building energy efficiency in China,comprising of 15 top-ranking universities and institutions in China.

Heat absorption control equation and its application of cool-wall cooling system in mines

In order to solve the heat damages in deep mines, a cool-wall cooling technology and its working model are proposed based on the principles of heat absorption and insulation in this paper. During this process, the differential equation of thermal equilibrium for roadway control unit is built, and the heat adsorption control equation of cool-wall cooling system is derived by an integral method, so as to obtain the quantitative relationship among the heat absorption capacity of cooling system, the heat dissipating capacity of surrounding rock and air temperature change. Then, the heat absorption capacity required by air temperature less than the standard value for safety is figured out by section iterative method with the simultaneous solution of heat absorption control equation and the heat dissipation density equation of surrounding rock. Finally, the results show that as the air temperature at the inlet of roadway is 25 ℃, the roadway wall is covered by heat-absorbing plate up to 39% of the area, as well as the cold water is injected into the heat-absorbing plate with a temperature of 20 ℃ and a mass flow of 113.6 kg/s, the air flow temperature rise per kilometer in the roadway can be less than 3 ℃.

Convective Heat and Mass Transfer in Water at Super－Critical Pressures under Heating or Cooling Conditions in Vertical Tubes

Forced and mixed convection heat and mass transfer are studied numerically for water containingmetallic corrosion products in a heated or cooled vertical tube with variable thermophysical propertiesat super-critical pressures. The fouling mechanisms and fouling models are presented. The influenceof variable properties at super-critical pressures on forced or mixed convection has been analyzed.The differences between heat and mass transfer under heating and cooling conditions are discussed. Itis found that variable properties, especially buoyancy, greatly influence the fluid flow and heat masstransfer.

Effects of Heat Treatment on Properties of Polyester Filaments

Many properties of polyester filaments such as heat shrinkage, tenacity, elongation at break and etc. are greatly influenced by drawing, so post-drawing is important in downstream processing. As more and more profile fibers and multi-variance fibers used in textile industry, the properties of above two kinds of differential polyester filaments after drawing in different heat conditions were studied. Finally following conclusions were obtained: Firstly, the tenacity and elongation at break decreases with the rise of Tp. Secondly, the tenacity rises but the elongation at break decreases with the increase of Tb. Then, when the Tb is low, both the shrinkage in boiling water and hi hot air decreases with the rise of Tp, while, when the Tb is high, both the shrinkage rises with the rise of Tp. The last, both the shrinkage decreases with the rise of Tb.

Mixed convective heat and mass transfer analysis for peristaltic transport in an asymmetric channel with Soret and Dufour effects

The present investigation addresses the simultaneous effects of heat and mass transfer in the mixed convection peristaltic flow of viscous fluid in an asymmetric channel. The channel walls exhibit the convective boundary conditions. In addition, the effects due to Soret and Dufour are taken into consideration. Resulting problems are solved for the series solutions. Numerical values of heat and mass transfer rates are displayed and studied. Results indicate that the concentration and temperature of the fluid increase whereas the mass transfer rate at the wall decreases with increase of the mass transfer Biot number. Furthermore, it is observed that the temperature decreases with the increase of the heat transfer Biot number.

Damage Action of Alkali-resistant Glass Fiber in Cement-based Material

The compressive strength and flexural strength with the same strength class cement mortar of the alkali-resistant glass fiber cement mortar were tested in standard and hot-water curing condition, and the damage mechanism of alkali-resistant glass fiber was studied. The interaction mechanisms of the chemical erosion and physical injury in different curing conditions were studied in order to summarize the damage mechanism of alkali-resistant glass fiber in cement-based materials, and chloride diffusivity coefficient and porosity of cement mortar were tested in the different curing conditions. The experimental results are that the strength of cement based materials and fiber cement slurry interface zone were closely related, and heat curing could accelerate the hydration of cement, but inevitably enlarge the defect.

A Study of Ca-Mg Silicate Crystalline Glazes——An Analysis on Forms of Crystals

In the study on Ca-Mg silicate crystalline glazes, we found some disequilibrated crystallization phenomena, such as non-crystallographic small angle forking and spheroidal growth, parasitism and wedging-form of crystals, dendritic growth, secondary nucleation, etc. Those phenomena possibly resulted from two factors: (1) partial temperature gradient, which is caused by heat asymmetry in the electrical resistance furnace, when crystals crystalize from silicate melt; (2) constitutional supercooling near the surface of crystals. The disparity of disequilibrated crystallization phenomena in different main crystalline phases causes various morphological features of the crystal aggregates. At the same time, disequilibrated crystallization causes great stress retained in the crystals, which results in cracks in glazes when the temperature drops. According to the results, the authors analyzed those phenomena and displayed correlative figures and data.

Optimization of Selecting Air Conditioning Cold/Heat Sources with Grey Relation Analysis

Selection of air conditioning（AC） cold/heat sources generally concerns about certain aspects and cannot reveal the whole profile of the problems. Grey relation analysis （GRA） is a data processing method to categorize the correlation extent of compared sequences and a certain reference sequence in a system with uncertain information. It is applied to evaluating and selecting AC cold/heat sources from four main aspects, which are technology, economy, reliability, and operation and management. Case study shows that the result for selecting AC cold/heat sources with the GRA method can be more reasonable and convincible. Thus it offers a new approach for designers in heating, ventilating and air conditioning field to compare and evaluate different AC cold/heat sou rces.

Characterization of Dissimilar Welding between 304 Stainless Steel and Gray Iron Using Nickel Coated Electrode

This paper presents the study carried out to study the microstructure and mechanical properties of AISI 304 stainless steel and gray iron, in order to recognize the effect of welding parameters on the joint. The shielded metal arc welding technique was applied with a 3.2 mm diameter nickel coated electrode under preheating and post heat conditions at 350&deg;C. Vickers hardness test and metallographic analysis were carried out at the heat affected zone and at the interface to determine the effect on mechanical and metallurgical characteristics. Vickers hardness differences among joint areas were directly related to microstructural changes. There are no significant differences in AISI 304 hardness, but the hardness increased at the heat affected zone and decreased at the filler metal. Grey iron hardness at the heat affected zone was even lower and more slightly superior than grey iron hardness.

HVAC energy cost minimization in smart grids: A cloud-based demand side management approach with game theory optimization and deep learning

In this paper, we present a novel cloud-based demand side management (DSM) optimization approach for the cost reduction of energy usage in heating, ventilation and air conditioning (HVAC) systems in residential homes at the district level. The proposed approach achieves optimization through scheduling of HVAC energy usage within permissible bounds set by house users. House smart home energy management (SHEM) devices are connected to the utility/aggregator via a dedicated communication network that is used to enable DSM. Each house SHEM can predict its own HVAC energy usage for the next 24 h using minimalistic deep learning (DL) prediction models. These predictions are communicated to the aggregator, which will then do day ahead optimizations using the proposed game theory (GT) algorithm. The GT model captures the interaction between aggregator and customers and identifies a solution to the GT problem that translates into HVAC energy peak shifting and peak reduction achieved by rescheduling HVAC energy usage. The found solution is communicated by the aggregator to houses SHEM devices in the form of offers via DSM signals. If customers’ SHEM devices accept the offer, then energy cost reduction will be achieved. To validate the proposed algorithm, we conduct extensive simulations with a custom simulation tool based on GridLab-D tool, which is integrated with DL prediction models and optimization libraries. Results show that HVAC energy cost can be reduced by up to 36% while indirectly also reducing the peak-to-average (PAR) and the aggregated net load by up to 9.97%.

Computational fluid dynamics simulation of friction stir welding:A comparative study on different frictional boundary conditions

Numerical simulation based on computational fluid dynamics （CFD） is a useful approach for quantitatively investigating the underlying thermal-mechanical conditions during FSW, such as temperature field and material deformation field. One of the critical issues in CFD simulation of FSW is the use of the frictional boundary condition, which represents the friction between the welding tool and the workpiece in the numerical models. In this study, three-dimensional numerical simulation is conducted to analyze the heat transfer and plastic deformation behaviors during the FSW of AA2024. For comparison purposes, both the boundary velocity （BV） models and the boundary shear stress （BSS） models are employed in order to assess their performances in predicting the temperature and material deformation in FSW. It is interesting to note that different boundary conditions yield similar predictions on temperature, but quite different predictions on material deformation. The numerical predictions are compared with the experimental results. The predicted deformation zone geometry by the BSS model is consistent with the experimental results while there is large difference between the predictions by the BV models and the experimental measurements. The fact that the BSS model yields more reasonable predictions on the deformation zone geometry is attributed to its capacity to automatically adjust the contact state at the tool/workpiece interface. Based on the favorable predictions on both the temperature field and the material deformation field, the BSS model is suggested to have a better performance in numerical simulation of FSW than the BV model.

Clustering compression-based computation-efficient calibration method for digital twin modeling of HVAC system

Digital twin is regarded as the next-generation technology for the effective operation of heating,ventilation and air conditioning(HVAC)systems.It is essential to calibrate the digital twin models to match them closely with real physical systems.Conventional real-time calibration methods cannot satisfy such requirements since the computation loads are beyond acceptable tolerances.To address this challenge,this study proposes a clustering compression-based method to enhance the computation efficiency of digital twin model calibration for HVAC systems.This method utilizes clustering algorithms to remove redundant data for achieving data compression.Moreover,a hierarchical multi-stage heuristic model calibration strategy is developed to accelerate the calibration of similar component models.Its basic idea is that once a component model is calibrated by heuristic methods,its optimal solution is utilized to narrow the ranges of parameter probability distributions of similar components.By doing so,the calibration process can be guided,so that fewer iterations would be used.The performance of the proposed method is evaluated using the operational data from an HVAC system in an industrial building.Results show that the proposed clustering compression-based method can reduce computation loads by 97%,compared to the conventional calibration method.And the proposed hierarchical heuristic model calibration strategy is capable of accelerating the calibration process after clustering and saves 14.6%of the time costs.

Upshot of Chemical Species and Nonlinear Thermal Radiation on Oldroyd-B Nanofluid Flow Past a Bi-directional Stretched Surface with Heat Generation/Absorption in a Porous Media

A three-dimensional mathematical model is developed to examine the flow of nonlinear thermal radiation Oldroyd-B nanofluid past a bidirectional linearly stretched surface in a porous medium. The flow is induced by temperature dependent thermal conductivity, chemical reaction and convective heat and mass conditions. Novel characteristics of Brownian motion and thermophoresis are accompanied by magnetohydrodynamic and heat generation/absorption.Self-similar transformations are employed to convert the system of nonlinear partial differential equations to a system of ordinary differential equations with high nonlinearity and are solved by strong analytic technique named as Homotopy Analysis method(HAM). Effects of varied arising parameters on involved distributions are reflected through graphical illustrations. From this study, it is perceived that strong magnetic field hinders the fluid's motion and leads to rise in temperature that eventually lowers heat transfer rate from the surface. Further, decrease in heat transfer rate is also observed for enhanced values of thermal radiation parameter. To validate our results, a comparison with already published paper in limiting case is also given and results are found in excellent oncurrence; hence reliable results are being presented.

Machine Learning and Deep Learning Methods for Enhancing Building Energy Efficiency and Indoor Environmental Quality – A Review

The built environment sector is responsible for almost one-third of the world’s final energy consumption. Hence, seeking plausible solutions to minimise building energy demands and mitigate adverse environmental impacts is necessary. Artificial intelligence (AI) techniques such as machine and deep learning have been increasingly and successfully applied to develop solutions for the built environment. This review provided a critical summary of the existing literature on the machine and deep learning methods for the built environment over the past decade, with special reference to holistic approaches. Different AI-based techniques employed to resolve interconnected problems related to heating, ventilation and air conditioning (HVAC) systems and enhance building performances were reviewed, including energy forecasting and management, indoor air quality and occupancy comfort/satisfaction prediction, occupancy detection and recognition, and fault detection and diagnosis. The present study explored existing AI-based techniques focusing on the framework, methodology, and performance. The literature highlighted that selecting the most suitable machine learning and deep learning model for solving a problem could be challenging. The recent explosive growth experienced by the research area has led to hundreds of machine learning algorithms being applied to building performance-related studies. The literature showed that existing research studies considered a wide range of scope/scales (from an HVAC component to urban areas) and time scales (minute to year). This makes it difficult to find an optimal algorithm for a specific task or case. The studies also employed a wide range of evaluation metrics, adding to the challenge. Further developments and more specific guidelines are required for the built environment field to encourage best practices in evaluating and selecting models. The literature also showed that while machine and deep learning had been successfully applied in building energy efficiency research, most of the studies are still at the experimental or testing stage, and there are limited studies which implemented machine and deep learning strategies in actual buildings and conducted the post-occupancy evaluation.