System Design Optimization Research Articles

Performance estimation of optical skin probe in short wavelength infrared spectroscopy based on Monte-Carlo simulation

Optical throughput and optical path length are key parameters to obtain high signal to noise ratio and sensor sensitivity for the detection of skin tissue components based on short wavelength infrared (SWIR) spectroscopy. These parameters should be taken into account at the stage of optical system design. We aim to develop a method to estimate the optical efficiency and the effective water path length of a newly designed SWIR spectroscopy skin measurement system using Monte-Carlo photon migration simulation. To estimate the optical efficiency and the effective water path length, we investigated the characteristics of Monte-Carlo photon migration simulation utilizing one layered simple skin model. Simulation of photon transport in skin was conducted for transmission, transflection, and reflection optical configurations in both first overtone (1540 ~ 1820 nm) and combination (2040 ~ 2380 nm) wavelength ranges. Experimental measurement of skin spectrum was done using Fourier transform infrared spectroscopy based system to validate the estimation performance. Overall, the simulated results for optical efficiency and effective water path length are in good agreements with the experimental measurements, which shows the suggested method can be used as a means for the performance estimation and the design optimization of various in-vivo SWIR spectroscopic system.

Research on optimization of index system design and its inspection method: data quality diagnosis, index classification and stratification

PurposeThe purposes of this research are to study the theory and method of multi-attribute index system design and establish a set of systematic, standardized, scientific index systems for the design optimization and inspection process. The research may form the basis for a rational, comprehensive evaluation and provide the most effective way of improving the quality of management decision-making. It is of practical significance to improve the rationality and reliability of the index system and provide standardized, scientific reference standards and theoretical guidance for the design and construction of the index system.Design/methodology/approachUsing modern methods such as complex networks and machine learning, a system for the quality diagnosis of index data and the classification and stratification of index systems is designed. This guarantees the quality of the index data, realizes the scientific classification and stratification of the index system, reduces the subjectivity and randomness of the design of the index system, enhances its objectivity and rationality and lays a solid foundation for the optimal design of the index system.FindingsBased on the ideas of statistics, system theory, machine learning and data mining, the focus in the present research is on “data quality diagnosis” and “index classification and stratification” and clarifying the classification standards and data quality characteristics of index data; a data-quality diagnosis system of “data review – data cleaning – data conversion – data inspection” is established. Using a decision tree, explanatory structural model, cluster analysis, K-means clustering and other methods, classification and hierarchical method system of indicators is designed to reduce the redundancy of indicator data and improve the quality of the data used. Finally, the scientific and standardized classification and hierarchical design of the index system can be realized.Originality/valueThe innovative contributions and research value of the paper are reflected in three aspects. First, a method system for index data quality diagnosis is designed, and multi-source data fusion technology is adopted to ensure the quality of multi-source, heterogeneous and mixed-frequency data of the index system. The second is to design a systematic quality-inspection process for missing data based on the systematic thinking of the whole and the individual. Aiming at the accuracy, reliability, and feasibility of the patched data, a quality-inspection method of patched data based on inversion thought and a unified representation method of data fusion based on a tensor model are proposed. The third is to use the modern method of unsupervised learning to classify and stratify the index system, which reduces the subjectivity and randomness of the design of the index system and enhances its objectivity and rationality.

A Review Regarding Combined Heat and Power Production and Extensions: Thermodynamic Modelling and Environmental Impact

This paper reports on a review on combined heat and power (CHP). A historical examination points out that combined heat and power was primarily used for hot heat valorizing (CHHP). The technological aspects evolved with this configuration first in industrial size. More recently, configuration with cold heat and power production (CCHP) appeared. Then, the immediate extension of this configuration led to trigeneration configuration, providing three useful effects: power and hot and cold heat. We suggest in the paper that progress regarding this last approach remains to be achieved towards the extension of trigeneration to polygeneration, whatever the form of energy and substance (water uses, for example). More generally, we consider that the goal, regarding the energy uses, is the integration of all needs in the design stage of the whole system (design optimization). Then, the evolution of the system in time should be considered, this being the purpose of control command of the optimized concern. This part remains to be developed in the future. Currently, the optimized design is well-started from the thermodynamic point of view with good criterion (efficiency), completed with economic and environmental objectives or constraints, as is reported in the review.

An innovative computational design for air impingement coupled radio frequency thawing process

Radio frequency (RF) processing, with its volumetric heating ability and a longer wavelength, is applied in industrial thawing and tempering processes for larger-sized frozen food products. However, overheating problems are observed at corners and edges of (specifically the sharp-edged foods) with a significant temperature non-uniformity, and tempering is preferred with its limited temperature increase right below the freezing point in most cases. The distance between the electrodes, charged electrode potential, and sample-electrode moving conditions in industrial-scale systems were investigated for temperature uniformity in the literature, but there has not been a confirmed solution presented for thawing yet. Therefore, air impingement coupled with RF heating was presented in this computational study using a previously (experimentally) validated model. Computational studies were carried out using Comsol Multiphysics for process design purposes, and RF system geometries included single and double cavity configurations with an air impingement speed of 0.5 and 2.5 m/s in a slot jet application. Significant temperature distribution uniformity was obtained within the samples even at higher electrode potentials, and air impingement coupled RF systems were presented for industrial-scale process conditions. 2750 V potential and 2.5 m/s air impingement speed were the optimal process condition for both single and double cavity RF systems. The results of this study are expected to be further used for system design and process optimization for industrial-scale RF thawing applications.

Hybrid Satellite-Terrestrial Networks toward 6G: Key Technologies and Open Issues.

Future wireless networks will be required to provide more wireless services at higher data rates and with global coverage. However, existing homogeneous wireless networks, such as cellular and satellite networks, may not be able to meet such requirements individually, especially in remote terrain, including seas and mountains. One possible solution is to use diversified wireless networks that can exploit the inter-connectivity between satellites, aerial base stations (BSs), and terrestrial BSs over inter-connected space, ground, and aerial networks. Hence, enabling wireless communication in one integrated network has attracted both the industry and the research fraternities. In this work, we provide a comprehensive survey of the most recent work on hybrid satellite-terrestrial networks (HSTNs), focusing on system architecture, performance analysis, design optimization, and secure communication schemes for different cooperative and cognitive HSTN network architectures. Different key technologies are compared. Based on this comparison, several open issues for future research are discussed.

DUET: A Novel Energy Yield Model With 3-D Shading for Bifacial Photovoltaic Systems

Bifacial photovoltaic (PV) performance models strive to accurately quantify rear-incident irradiance. While ray tracing models are optically rigorous, they require significant computational resources; faster view factor (VF) models are widely adopted but require user-defined loss factors to approximate rear shading and irradiance nonuniformity, introducing uncertainty in energy yield predictions. This article describes DUET—a bifacial PV performance model that calculates optical and electrical performance based on a physically representative array geometry. DUET’s novel shading algorithm pairs a 3-D VF model with deterministic ray-object intersections to capture 2-D shade-inclusive irradiance profiles while minimizing computational cost. Series and parallel combination of current–voltage curves capture irradiance nonuniformity throughout the module and array. This article provides validation against open-access system measurements from a test site in Roskilde, Denmark, and comparison to other software tested there [1]. DUET’s modeled bifacial energy yield agrees with measured data within −1.56% for fixed-tilt and −0.65% for horizontal single-axis tracked (HSAT) systems. Mean absolute error (MAE) in hourly bifacial power is 14.2–15.0 mW/Wp for fixed-tilt and 17.3–18.3 mW/Wp for HSAT, depending on the module temperature model applied. Comparing modeled and measured rear irradiance of two rear-facing pyranometers, DUET’s MAE values of 2.8 W/m <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$^{2}$</tex-math></inline-formula> for fixed-tilt and 3.7 W/m <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$^{2}$</tex-math></inline-formula> for HSAT are among the lowest errors reported for other software tested at this site. DUET provides computationally efficient bifacial performance modeling with geographic, temporal, and structural specificity to determine loss factors for use in other performance models or to be used directly in system design optimization.

Optimisation of cogeneration system design with extended automated targeting model (ATM)

In this work, a mathematical optimisation technique known as automated targeting model (ATM) was extended for techno-economic evaluation of gas turbine (GT), steam turbine and combined cycle CHP systems. The objective is to introduce a systematic methodology for rigorous targeting of steam and power generation from complex CHP systems. In particular, the non-linear model of GT was linearised and incorporated for use in ATM. The extended ATM was applied to target minimum total annualised cost (TAC) for CHP systems in various scenarios. The extended technique was demonstrated with case studies of glycerine distillation and oleochemical plants. For the glycerine distillation plant, the result showed that combined cycle CHP system is the most cost-effective and environmental friendly scheme for the scenario, with minimum TAC of $ 5,668,000/y and carbon footprint of 69,008 t CO2e/y. In Scenario 1 of the oleochemical plant case study, with constant steam and power demand, the result showed that GT-CHP is the most cost-efficient scheme with minimum TAC and carbon footprint of $ 2,184,000/y and 24,363 t CO2e/y respectively. Meanwhile, for Scenario 2 with fluctuating steam and power demand according to plant production capacity, which is more realistic, its minimum TAC for GT-CHP only increases by 2 %. The new approach allows the identification of the optimum mode of operation at different demand conditions.

Frequency-Band Design and Parameter Optimization of MCRWPT System Based on Particle Swarm Optimization

Frequency-Band Design and Parameter Optimization of MCRWPT System Based on Particle Swarm Optimization

LOW POWER OPTIMIZATION OF FULL ADDER CIRCUIT BASED ON GDI LOGIC FOR BIOMEDICAL APPLICATIONS

Advanced Electronic Devices have recently become more prevalent, designers have opted for low power, quick speed, and compact designs and processes. Even though there are numerous design methodologies currently in use for VLSI system design optimization, very few design techniques produce solutions that are optimally optimal. GDI-based circuits are becoming increasingly important since they use less space, power, and energy. The GDI technique ensures minimal propagation delay, power, and area in low-power design strategies. For 45nm technology, the Cadence Virtuoso EDA tool is utilised to determine delay and power. The proposed designs examination of delay and power performance at 1.0V voltage produced positive findings. The Gate Diffusion Input concept serves as the foundation for the proposed design in this work. In order to achieve a full voltage swing of the output, a 1-bit full adder circuit design using GDI is demonstrated in this work. The GDI with the Full Swing Technique is presented in this work. Applying the suggested way to a 45nm complete adder from 14 Transistors. It is evident from the obtained simulation results that the suggested design uses the least power and the least amount of delay when compared to other full adder circuits that are already in use. Consequently, compared to previous full adder GDI circuit designs, the output voltage swing is in full and the overall power-delay product is improved by 60 percent.

Physics-informed optimization of robust control system to enhance power efficiency of renewable energy: Application to wind turbine

This study mainly focused on wind turbine (WT) design in urban environments because the negative torque generated by the returning wind blade profile was the primary cause of its low power efficiency. The turbine chosen in this study was a vertical-axis wind turbine (H-VAWT). However, the physics-informed optimization of the robust control system (RCS) design of the WT was challenging because the rotor blades (NACA 0012 airfoil) had nonlinear aerodynamic characteristics. Furthermore, our proposed controller was used in this study because of its ability to suppress disturbances and ensure stability against various uncertainties. The electrical block setup used an H-type VAWT based on advanced direct vector control generators. This indicated that a low-inertia turbine was more acceptable than a high-inertia turbine because of its suitability for maximum power conversion. Overall, there was a substantial active power gain of approximately 25% greater than conventional control systems.

Design and multi-scenario optimization of a hybrid power system based on a working gas turbine: Energy, Exergy, Exergoeconomic and Environmental evaluation

The rising demand for electricity, along with the need to minimize carbon footprints, has motivated academics to investigate the flexible and efficient integration of energy conversion technologies. A novel hybrid power generation system based on environmentally friendly and cost-effective technologies to recover the waste heat of a working gas turbine is designed and assessed in different scenarios of multi-objective optimization from energy, exergy, exergoeconomic, and environmental (4E) perspectives. In the proposed system, a steam methane reformer and a water gas shift reactor are utilized for hydrogen production, while a polymer electrolyte membrane fuel cell (PEMFC) and steam/organic Rankine cycles are run for generating additional power. Aspen Plus, in conjunction with Fortran, Microsoft Excel, and MATLAB, is used to model and simulate the designed plant. The response surface methodology (RSM) is utilized to determine accurate surrogate models to describe the evaluation criteria, and the Non-dominated Sorting Genetic Algorithm II technique is employed to seek the optimal conditions. Moreover, TOPSIS and LINMAP decision-making approaches are used to find the best final solution among Pareto frontiers. The analysis of variance (ANOVA) and sensitivity analysis are also applied to evaluate the importance of the design variables. In this regard, three single-objective optimizations and four multi-objective optimization scenarios based on the maximization of the ecological coefficient of performance (ECOP) and the minimization of CO2 emissions and total system product cost (Ċp) are carried out. It is demonstrated that the system’s evaluation criteria have the highest and lowest sensitivity to the variation of reformer temperature and ORC pressure, respectively. From the triple-objective optimization procedure, the decision variables including reformer temperature, ORC pressure, Rankine cycle I pressure, and Rankine cycle II pressure are 544 °C, 4.35 bar, 158.12 bar, and 52.82 bar, respectively. At these conditions, the total hybrid system’s energy efficiency, exergy efficiency, exergy destruction, net generated power, and total investment cost rate are 45.96%, 46.83%, 215.72 MW, 203.67 MW, and 9791 $/h, respectively. The findings of this paper conclude that it is necessary to address all objective functions simultaneously in the system’s ultimate optimum design. Furthermore, the objective of this paper becomes even more apparent when there is no choice but to cut greenhouse gas emissions while also addressing the rising global energy demand.

Performance analysis of flexible flow shop with parallel manufacturing cells

Performance evaluation for stochastic manufacturing systems is significant for system design optimization, but it is difficult to exactly analyse these systems with general arrival processes and service times. This paper studies a flexible flow shop with parallel manufacturing cells and models it as a queueing network. Parallel manufacturing cells and finite pallets lead to strong dependence among stages, and existing methods cannot be directly employed in this problem. Thus, approximate analysis is proposed to estimate performance measures of the flexible flow shop with parallel manufacturing cells based on two-moment approximations for a parallel-input synchronization station and an aggregation procedure. Numerical studies show the accuracy and the efficiency of the proposed method by comparing it with simulation results of experiments. This work can provide a basis to analyse and design more complex manufacturing systems.

Thermal management optimization of the photovoltaic cell by the phase change material combined with metal fins

Regulating photovoltaic (PV) cells temperature using phase change materials (PCMs) is considered a promising thermal management strategy. In this study, a solar PV-PCM collector with rectangular copper fins was proposed, and the effects of the PCM height and fin length, arrangement, and number, on the temperature characteristics, and electrical efficiency of PV cells were numerically investigated. A PCM height of 60 mm could meet the thermal management requirement of a heat flux input of 800 W/m2 during the daytime. Compared with the PV-PCM model without fins, the PV cell performance was improved by 4.62% for the model uniformly arranged three fins with a height of 33.33 mm. The variable length and nonuniform arrangement of fins could further enhance the performance of PV cells; however, the temperature uniformity deteriorated. Compared with fin length and arrangement, the fin number played a more significant role in the thermal management of PV cells. The model with eleven fins performed the best with the average temperature, temperature unevenness, and efficiency of 48.58 °C, 3.20, and 11.19%, respectively. These values were 16.11 °C and 43.06% lower, and 7.70% greater than the model without fins. This study provides valuable insight into the design optimization of PV-PCM systems.

Design optimization of district heating systems: A review

District heating systems offer the possibility of lowering emissions and support the goal of reaching a carbon-neutral energy system by integrating renewable heat sources. Therefore, this work provided a systematic literature review to identify potential research gaps and show the literature distribution over the relevant topics. The focus is on the design optimization with (non-)linear programming of district heating systems in the context of decarbonization. Furthermore, crucial energy balance equations were extracted from the literature for a potential optimization problem. The systematic literature review limited its search to two databases, 10 years timespan, a quality measure, and uses keywords regarding topic and method. Categories were derived based on the subject and literature to cluster the found publications and identify potential research gaps. The results showed potential research gaps in the depiction of different stakeholder decisions, reduction of computational efforts, and their resulting uncertainties. Additionally, they identified gaps in the integration of low-grade heat sources, thermal storage facilities, and energy converters, especially geothermal energy, large-scale heat pumps, and seasonal storages.

A New Approach to System Design Optimization of Underwater Gliders

System design optimization of an underwater glider involves various disciplines, such as hydrodynamics, structure, sizing, control, power, payload, and trajectory, which overlap with each other and influence the endurance of the system. Compared with traditional optimization methods, multidisciplinary design optimization provides a more efficient method for complex engineering problems involving overlapping disciplines. This article establishes a universal disciplinary framework of an underwater glider after the system analysis, which involves five disciplines, including hydrodynamic shape, pressure hull, buoyancy, attitude, and energy. To decouple the relationship among these disciplines and improve the efficiency of optimization, approximate models in the disciplines of hydrodynamic shape and pressure hull are established. After the coupling analysis, a novel approach is proposed for the system design optimization of an underwater glider, in which the concurrent subspace optimization, penalty function method, and the multipopulation genetic algorithm are combined together. The approach proposed in this article can meet the diversified design requirements of underwater gliders in different observation missions, which is verified by a sea trial of an improved Petrel-L glider.

Thermodynamic and exergoeconomic analysis of a proton exchange membrane fuel cell/absorption chiller CCHP system based on biomass gasification

This work investigates an integrated system consisting of biomass gasification process, proton exchange membrane fuel cell (PEMFC) and absorption chiller. The proposed system is studied from the energetic and exergoeconomic point of view. In addition, parametric analysis and uncertainty analysis are carried out to investigate the effects of four key operational parameters and three uncertain parameters. System energy efficiency and exergy efficiency are obtained as 57.41% and 18.07%, respectively. 21.46% of the electricity production is consumed by auxiliary components of the PEMFC stack. Largest exergy destruction is in the gasifier and the stack, due to significant irreversibility of chemical/electrochemical reactions. Exergoeconomic results indicate that in the selective oxidation process, investment cost is much higher than the cost rate of exergy destruction. While gasifier, anode/cathode heat exchangers and humidifiers, condenser, solution heat exchangers and valves have poor exergetic performance. High current density, operation temperature and moisture content are unfavorable for exergy efficiency. Extension of operation life, lower interest rate and lower maintenance factor can guarantee a desired system exergoeconomic performance. This research provides pragmatic information about thermodynamic and exergoeconomic performance of this integrated system. Obtained results are important for system design and operational optimization on various PEMFC coupled polygeneration systems.

Bayesian support vector machine for optimal reliability design of modular systems

In a modular system, uncertainties will spread among coupled modules and cause system failure. To cope with this issue, the reliability-based design optimization (RBDO) of modular systems came into being. However, the solution of this design task is a nested triple-loop process, making the computational burden unaffordable for real-world systems. Thus, this paper endeavors to effectively mitigate this computational effort. The individual module feasible approach is first proposed to tackle the coupling effects of modules, whereby, the original optimization problem is converted into a conventional one. Then, the Bayesian-inference-based support vector machine is utilized to build the alternative model for the actual probabilistic constraint function, in the augmented reliability space. The alternative model is constructed using small number of model evaluations, which possesses enough precision everywhere in the augmented confidence region. Finally, the optimal decision scheme is obtained by solving the formulated conventional RBDO using the alternative model. The performance of the proposed method is investigated using several examples.

Collaborative Control and Optimization Mechanism of Thermal Management of New Energy Vehicles

Global issues such as global warming, rising sea level, melting Arctic and Antarctic glaciers, deterioration of the natural environment, and depletion of fossil energy have attracted increasing attention. As the concept of environmental protection has become increasingly popular, the concept of new energy automobiles has been proposed to keep the heat up. Especially in recent years, with the advantages of energy conservation, environmental protection, and low noise, new energy automobiles have changed from concept to industry and have been generally accepted and recognized by consumers in the consumer market. The increasingly stringent energy crisis and emission regulations have put forward more stringent requirements for modern automobiles. The thermal management of the new generation of intelligent automobiles is not only limited to simply solving the problem of engine heat dissipation but also involves reliability, power, economy, emissions, and comfort. It is an important vehicle development technology with many performances such as performance. The integrated thermal management of new energy vehicles includes engine cooling, oil cooling, air conditioning refrigeration, HVAC heating, supercharged intercooling, low cycle thermal fatigue, and thermal damage. For new energy vehicles such as hybrid and pure electric vehicles, it also includes motor cooling, motor controller cooling, and power battery temperature control. For the purpose of vehicle thermal management optimization design, this paper innovatively proposes IVTM technical solutions, relying on multidimensional numerical calculation coupling and multiobjective collaborative optimization control to integrate system design, scheme evaluation, performance analysis, dynamic control, and collaborative optimization. Through the integrated thermal management collaborative control strategy based on the full operating conditions of the new energy vehicle, the comprehensive improvement of multiple evaluation indicators such as system design performance, thermal management, and control performance and economy is achieved.

Logic design method and optimization of hydraulic system for heavy-duty automatic transmission

In this paper, the shifting control hydraulic system of the heavy-duty automatic transmission was designed, aiming to unify and standardize design methods. The said system was designed according to the binary logic characteristics of hydraulic components. In addition, to meet the torque transmission requirements and reduce the energy consumption, both the oil pressure supply and flow-regulating system were designed. Mathematical and simulation models of the hydraulic system were established to analyze its performance. Finally, the genetic algorithm was used to optimize the system (within the AMESim environment); the results have shown that the main pressure of each gear was controlled in a reasonable range, and both the pressure of shift clutch and the pressure response time were reduced. In addition, the power loss of the hydraulic system was significantly improved, which improved the practical performance of the overall hydraulic system.

Geotechnical RBDO: Coupling the inverse reliability algorithm with multi-objective reliability-based design optimization of geotechnical systems

The analysis and design of geotechnical engineering inevitably deal with various sources of uncertainties. To further expand the application of reliability methods in geotechnical engineering design works, the inverse reliability algorithm is modified to incorporate unknown geotechnical design parameters in this paper. Based on the established HLRF algorithm for first order reliability analysis, the proposed approach can easily realize traditional single-objective inverse reliability-based design (RBD). Further, the multi-objective inverse reliability design is achieved by combining several single-objective inverse reliability analysis modules through a coupling matrix without seeking for any other surrogate functions. The Nataf transformation is integrated into the method to deal with the correlation of random variables. In addition, the algorithm can be combined with any nonlinear optimization method when the number of design parameters is greater than the number of performance functions, at which point the RBD is extended to reliability-based design optimization (RBDO) with an objective function related to the optimum design purpose. Verifications of the proposed approach are illustrated through several examples, which show that the proposed reliability design optimization framework is effective and can be used as a basic tool for RBDO problems in geotechnical engineering.