early design stage
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Buildings ◽  
2021 ◽  
Vol 11 (12) ◽  
pp. 651
Author(s):  
Seung-Hyo Baek ◽  
Byung-Hee Lee ◽  
Myoung-Souk Yeo

Renewable energy system (RES) is an environmentally friendly source of energy. A suitable design of RES is crucial to implement an energy-efficient building such as a zero energy building (ZEB). The significance of appropriate decision-making for the successful implementation of energy-efficient buildings has been increasing. In addition, the identification of the sizing of RES is equally important for architects or HVAC engineers. In this study, a novel sizing method for a single U-tube ground heat exchanger (GHE) is proposed. A transient thermal analysis for a single GHE is performed by considering ground temperature recovery effect as well as other major design parameters. The results are used to design the proposed sizing method and were verified by transient simulations for different design cases. Additionally, it was observed that the coefficient of variation of root mean square error (CV(RMSE)) for all ten design cases was lower than 15% during the heating and cooling seasons. Thus, the proposed design method can be used for sizing a GHE in the early design stage.


Author(s):  
Freia Harzendorf ◽  
Ralf Schelenz ◽  
Georg Jacobs

AbstractThe drivetrain as an important part of wind turbines needs to be improved in order to deal with today’s high development and cost pressure. One important step towards enhanced drivetrains is to identify the most suitable concept for a targeted onshore application in an early design stage. With this purpose, a holistic lifecycle system evaluation approach relying on minimum input information is presented. In order to identify a dominant solution, an additive target system is defined taking cost, ecological sustainability, and supplied energy into account. This multi-criteria decision is aggregated by defining a macrosocial evaluation criterion: “drivetrain specific energy supply effort”. A physics- and empirically-based model is developed to quantify the targets for different onshore drivetrain concepts. The validity of the model results is shown by a comparison to meta-analysis findings. Being utilized on a drivetrain concept comparison between geared and direct drive the approach’s value is showcased. Both concepts score on a comparable level slightly differing in weak and strong wind regimes. An exemplary trade-off between investment- and operational effort shows, that for both concepts the investment effort is higher than the operational. The comparison furthermore shows how robust decision support can be provided by parameter variation and finally it stresses, that the decision maker’s preferences need to be incorporated in the decision. Concluding, this analysis shows that physics- and empirically-based model approaches enable holistic wind turbine drivetrain concept comparisons in an early design stage.


2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Chiara Bedon ◽  
Silvana Mattei

In engineering applications, human comfort fulfillment is challenging because it depends on several aspects that can be mathematically controlled and optimized, like in case of structural, energy, or thermal issues, and others. Major troubles can indeed derive from combined human reactions, which are related to a multitude of aspects. The so-called “emotional architecture” and its nervous feelings are part of the issue. The interaction of objective and subjective parameters can thus make the “optimal” building design complex. This paper presents a pilot experimental investigation developed remotely to quantify the reactions and nervous states of 10 volunteers exposed to structural glass environments. As known, intrinsic material features (transparency, brittleness, etc.) require specific engineering knowledge for safe mechanical design but can in any case evoke severe subjective feelings for customers, thus affecting their psychological comfort and hence behaviour and movements. This study takes advantage of static/dynamic Virtual Reality (VR) environments and facial expression analyses, with Artificial Intelligence tools that are used to measure both Action Units (AUs) of facial microexpressions and optical heart rate (HR) acquisitions of volunteers exposed to VR scenarios. As shown, within the limits of collected records, the postprocessing analysis of measured signals proves that a rather good correlation can be found for measured AUs, HR data trends, and emotions under various glazing stimuli. Such a remote experimental approach could be thus exploited to support the early design stage of structural glass members and assemblies in buildings.


Author(s):  
Neerja Singh ◽  
Gaurav Verma ◽  
Vijay Khare

Nowadays, high-end Field-Programmable Gate Arrays (FPGAs) are capable of implementing relatively high-performance systems in the field of Digital Signal Processing (DSP). Due to the abundant application of multipliers, their implementation efficiency and performance have become a critical issue in designing the DSP systems. On the other hand, FPGAs consume a large amount of power due to their complex circuitry. So, the power estimation of FPGA implementations at an early design stage has become a critical design metric. Various models are available in the literature based on Look-up Tables (LUTs), but not much literature is available on speed-optimized multiplier design using DSP slices only. In this paper, an embedded multiplier (12.0 IP core) has been analyzed and customized for different Input/Output (I/O) configurations to estimate the power using Vivado Design Suite (2014.4) targeted to the Zynq-family FPGA device (Zynq evolution and development kit). The embedded multiplier IP has been optimized for performance using two different approaches, i.e., Mults (DSP)-based and LUTs-based. Post-synthesis attributes have been used for formulating the power estimation models based on Artificial Neural Network (ANN) and curve fitting and regression technique. The power values estimated from the proposed models have been authenticated with reference to those assessed from the commercial tool. Based on the results obtained, ANN-based model provides average errors of 0.73% and 0.88% for the LUTs and DSP-based designs, respectively. Whereas, the model based on curve fitting and regression technique provides average errors of 3.61% and 1.59% for the LUTs and DSP-based designs, respectively. The timing analysis has been done to get the design performance and time complexity of the proposed models. Area analysis of the design has also been performed in order to report the resource utilization.


2021 ◽  
Vol 9 ◽  
Author(s):  
Longwei Zhang ◽  
Chao Wang ◽  
Yu Chen ◽  
Lingling Zhang

Large-space buildings feature a sizable interface for receiving solar radiation, and optimizing their shape in the early design stage can effectively increase their solar energy harvest while considering both energy efficiency and space utilization. A large-space building shape optimization method was developed based on the “modeling-calculation-optimization” process to transform the “black box” mode in traditional design into a “white box” mode. First, a two-level node control system containing core space variables and envelope variables is employed to construct a parametric model of the shape of a large-space building. Second, three key indicators, i.e., annual solar radiation, surface coefficient, and space efficiency, are used to representatively quantify the performance in terms of sunlight capture, energy efficiency, and space utilization. Finally, a multi-objective genetic algorithm is applied to iteratively optimize the building shape, and the Pareto Frontier formed by the optimization results provides the designer with sufficient alternatives and can be used to assess the performance of different shapes. Further comparative analysis of the optimization results can reveal the typical shape characteristics of the optimized solutions and potentially determine the key variables affecting building performance. In a case study of six large-space buildings with typical shapes, the solar radiation of the optimized building shape solutions was 13.58–39.74% higher than that of reference buildings 1 and 3; compared with reference buildings 2 and 4, the optimized solutions also achieved an optimal balance of the three key indicators. The results show that the optimization method can effectively improve the comprehensive performance of buildings.


2021 ◽  
Vol 40 (3) ◽  
pp. 437-448
Author(s):  
M.I. Abubakar ◽  
Q. Wang

Discrete Event Simulation (DES) tool is commonly used for the design, analysis, and evaluation of manufacturing systems. Human centred assembly systems offer better system flexibility and responsiveness due to inherent human intelligence and problem-solving abilities; human can deal with product variations and production volumes; and can always adapt themselves to multiple tasks after learning process. Nevertheless, human performance can be unpredictable, and may alter over time due to varying psychological and physiological states, these are often overlooked by researchers when designing, implementing, or evaluating a manufacturing system. In this paper a user-friendly integrated DES method was proposed to enable manufacturing system designers to investigate overall performance of human centred system considering effects of selected human factors. the method can permit manufacturing system designers to evaluate overall manufacturing system performance with considerations of parameters of human factors at early design stage. A case study was carried out using integrated approach; simulation results demonstrate the applicability of this approach.


2021 ◽  

The absence of existing standards for product recovery planning and the associated difficulty in prioritising the conflicting design requirements are among the main challenges faced during product design. In this paper, a concept for the Design for Multiple Life-Cycles (DFMLC) is proposed to address this situation. The objective of the DFMLC model is to assist designers in evaluating design attributes of Multiple Life-Cycle Products (MLCP) at the early design stage. The methodology adopted for the evaluation of MLCP design strategies has been based on a modified Analytical Hierarchy Process (AHP). Two mapping matrices of the design guidelines and design strategies concerning MLCP design attributes were developed for the modified AHP model. Disassemblability (> 21 %) was found to be the most important design element for MLCP followed by serviceability (> 20 %) and reassembly (> 12 %).


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