Design Variables Research Articles

Thermal comfort, daylight, and energy performance of envelope-integrated algae-based bioshading and static shading systems through multi-objective optimization

Energy-efficient envelopes integrated with different shading devices, as noticeable passive design strategies, have been of great interest for research studies. However, there is a lack of attention on optimizing envelope-integrated novel algae-based bioshading systems (ABBS) in comparison with other shading devices to enhance buildings’ sustainability-oriented performances. Integrating microalgae culture system with building façade as a state-of-the-art bioshading system is among recent developments in high-performance architecture. Although, challenges/limitations concerning different performances of this technology have not been extensively addressed. The present study conducts a multi-objective optimization framework to investigate the Thermal Comfort Percentage (TCP), Useful Daylight Illuminance (UDI), and Energy Usage Intensity (EUI) in a school building to evaluate the relationship between the performance objectives and design variables (shading characteristics, window-to-wall ratio (WWR)) through comparing different static shading systems and ABBS in the hot (BSh) and cold semi-arid (BSk) climates. The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method was also applied to determine the best design options within Pareto frontiers. Results demonstrated that horizontal louver by 128.52 % TCP, 15.10 % UDI improvement in south-oriented façade in BSk, and overhang with fin (OF) by 18.99 % EUI reduction in southern facade in BSh climates contribute the most to enhance the objective metrics. Also, ABBS was not a stand-first system to enhance all the objective metrics compared to the other shading systems in none of the examined climates. Sensitivity analysis indicated that WWR has the most significant positive impact on EUI compared to the other studied metrics in almost all design options.

Pengaruh Desain Stasiun Kerja Dengan Pendekatan Participatory Ergonomics untuk Meningkatkan Produktivitas Karyawan: Studi Kasus SMK Az-Zawiyah Tanjung Batu

In the context of education, the success of an institution is not only determined by the quality of curriculum and teaching, but also by adequate working environment conditions. Therefore, this study aims to investigate the effect of workstation design with a participatory ergonomics approach on employee productivity in the teachers' room and principal's room. The result of this study is that there is an influence of workstation design elements, layout and physical environment on the application of Participatory Ergonomics in improving employee productivity of SMK Az-Zawiyah Tanjung Batu. This is because the sig t value of the workstation design variable is 0,007 < α = 0,05, the layout variable is 0,012 < α = 0,05, and the physical environment variable is 0,009 < α = 0,05. There is a joint influence (simultaneously) elements of workstation design, layout, and physical environment on employee productivity SMK Az-Zawiyah Tanjung Batu this is because the sig value F variable workstation design, layout, and physical environment amounted to < 0,001 < α = 0,05.

Prediction of rock fragmentation in a fiery seam of an open-pit coal mine in India

Spontaneous combustion of coal increases the temperature in adjoining overburden strata of coal seams and poses a challenge when loading blastholes. This condition, known as hot-hole blasting, is dangerous due to the increased possibility of premature explosions in loaded blastholes. Thus, it is crucial to load the blastholes with an appropriate amount of explosives within a short period to avoid premature detonation caused by high temperatures of blastholes. Additionally, it will help achieve the desired fragment size. This study tried to ascertain the most influencial variables of mean fragment size and their optimum values adopted for blasting in a fiery seam. Data on blast design, rock mass, and fragmentation of 100 blasts in fiery seams of a coal mine were collected and used to develop mean fragmentation prediction models using soft computational techniques. The coefficient of determination (R2), root mean square error (RMSE), mean absolute error (MAE), mean square error (MSE), variance account for (VAF) and coefficient of efficiency in percentage (CE) were calculated to validate the results. It indicates that the random forest algorithm (RFA) outperforms the artificial neural network (ANN), response surface method (RSM), and decision tree (DT). The values of R2, RMSE, MAE, MSE, VAF, and CE for RFA are 0.94, 0.034, 0.027, 0.001, 93.58, and 93.01, respectively. Multiple parametric sensitivity analyses (MPSAs) of the input variables showed that the Schmidt hammer rebound number and spacing-to-burden ratio are the most influencial variables for the blast fragment size. The analysis was finally used to define the best blast design variables to achieve optimum fragment size from blasting. The optimum factor values for RFA of S/B, ld/B and ls/ld are 1.03, 1.85 and 0.7, respectively.

Multi-objective optimization of a novel dynamic concentrated skin system considering daylight, building skin capacity, and visual space

Transmissive concentrator technology can solve the problems of expression of building skin form, maximized use of solar energy, and natural lighting inside the building that arise from integrating traditional photovoltaic technology. However, the advantages mentioned above interact and cannot be maximized to solve multiple problems simultaneously. Therefore, it becomes crucial to address the relationship between them optimally and improve the quality of the building and the environment. This study used grasshopper, ladybug, and multi-objective optimization tools to develop and analyze a transmission concentrator module integrated into an office building skin. An optimization framework for dynamic concentrating skins is constructed by modifying important design variables, resolving conflicting relationships between energy output, daylight quality, and visual space, and computing optimal solutions to multiple problems. The results show that the concentrated skin scheme, compared with the common skin and no skin scheme, can reduce the likelihood of glare by an average of 59.35% and 88.40%, respectively, and improve the useful daylight illuminance by an average of 2.40% and 16.25%, respectively, while providing the user with a visual field rate of about 80.54%, in the presence of higher energy output. In addition, thanks to the variation of the concentrating skin variables, using the recommended value of optimal interval and the most significant variables can better resolve the relationship between environment and energy and obtain optimal overall performance and solutions. This study provides data and methods for the integrating design of concentrating skin and optimizing indoor daylighting, which is expected to reduce carbon emissions.

Parametric study for optimizing fiber‐reinforced concrete properties

AbstractConcrete with fiber reinforcement is stronger and more ductile than concrete without reinforcement. Significant efforts have been made to demonstrate the properties and enhancements of concrete after reinforcement with various types and shapes of fibers. However, the issue of optimization in the reinforcement process is still unanswered. There is no academic study in the literature now available that can pinpoint the ideal fiber type, quantity, and shape and, more crucially, the overall technical viability of the reinforcement. The parametric analysis in this study determines the ideal shape, size, and proportion of fibers. The input and output parameters were separated from the optimization design variables. Input parameters included assessment of samples of fresh and mechanical concrete properties and the influence of type, length, and percentage of fiber on concrete performance. The aim was to establish the most efficient relationship between fiber dose and dimension to optimize the combined responses of workability and splitting tensile, flexural, and compressive strength. The mechanical and fresh properties of concrete reinforced with four different fibers, PFRC‐1, PFRC‐2, SFRC‐1, and SFRC‐2, were tested. The analysis showed that SFRC‐2‐20 mm‐1%, with compressive, split tensile, flexural, and workability values of 44.7 MPa, 3.64 MPa, 5.3 MPa, and 6.5 cm respectively, was the most effective combination among the materials investigated. The optimization technique employed in this study offers new, important insights into how input and output parameters relate to one another.

Determining the Gear Design Parameters Which Have Strong Correlation with Gear Volume and Contact Ratio for Helical Gear Design Optimization

The market has a significant demand for low-cost, compact size, extended fatigue life and high load-carrying capacity helical gears. One way to manufacture such gears is by minimizing gear volume and maximizing contact ratio. Most researchers focus on gear design optimization, but minimal study has been conducted to identify design variables that significantly impact gear volume and contact ratio. Hence, it is crucial to determine gear design parameters that strongly correlate with gear volume and contact ratio beforehand. A single-stage helical gear train of local electric multiple units (EMU) is used as the gear model, and the calculations are done based on ISO 6336. Seven parameters have been chosen as independent variables; module, number of teeth of pinion, gear ratio, helix angle, tooth thickness factor, normal pressure angle and addendum factor. Graphs of total gear volume and contact ratio against independent variables are plotted to examine their relationship. The results indicate that normal module, number of teeth of the pinion, and gear ratio strongly correlate with the total gear volume. Meanwhile, the number of teeth of pinion, helix angle, tooth thickness factor, normal pressure angle and addendum factor strongly correlate with contact ratio. Therefore, these design parameters must be considered to improve the accuracy of the gear design optimization model, which aims to optimize gear volume and contact ratio.

Optimization Analysis of the Shape and Position of a Submerged Breakwater for Improving Floating Body Stability

Submerged breakwaters can be installed underneath floating structures to reduce the external wave loads acting on the structure. The objective of this study was to establish an optimization analysis framework to determine the corresponding shape and position of the submerged breakwater that can minimize or maximize the external forces acting on the floating structure. A two-dimensional frequency-domain boundary element method (FD-BEM) based on the linear potential theory was developed to perform the hydrodynamic analysis. A metaheuristic algorithm, the advanced particle swarm optimization, was newly coupled to the FD-BEM to perform the optimization analysis. The optimization analysis process was performed by calling FD-BEM for each generation, performing a numerical analysis of the design variables of each particle, and updating the design variables using the collected results. The results of the optimization analysis showed that the height of the submerged breakwater has a significant effect on the surface piercing body and that there is a specific area and position with an optimal value. In this study, the optimal values of the shape and position of a single submerged breakwater were determined and analyzed so that the external force acting on a surface piercing body was minimum or maximum.

A hybrid path-following approach for constrained nonlinear-buckling optimization of variable stiffness composite shells with shape imperfections

Nonlinear buckling optimization of variable stiffness (VS) composite shells is computationally expensive due to frequent nonlinear analyses. Although the generalized path-following method can serve to reduce the redundant computation, it is weakened by two kinds of discontinuity. First, the design variables may not always be searched continuously in the constrained optimization. Second, the critical buckling states may not be continuous at singular points on the search path. To address this issue, a hybrid path-following approach is proposed to trace the critical buckling states in the nonlinear-buckling optimization with constraints on the realizability of the lamination parameters and the amplitude range of geometric imperfections. Firstly, the optimal search direction is determined with the sensitivity analysis of the critical buckling equations in the isogeometric continuum shell model. Then, a continuous following strategy is adopted to provide a proper initial estimate for the Newton iterations at a disconnected point. Moreover, an investigation into the singularity of the critical buckling equations is conducted to identify the discontinuous points of the critical states in a line-search. Upon detection of the singularity, a segment of path in state space is inserted to recover the continuity. Numerical experiments show that the continuity of the critical states in the optimization is well maintained, which leads to a more efficient optimization for the VS shell with shape imperfections.

WrapToR shells: Concept introduction, experimental testing, and design space exploration

This work introduces a novel truss stiffener concept for lightweight structural panels as an alternative to sandwich panels or stringer stiffened panels. The Wrapped Tow Reinforced (WrapToR) truss concept is modified to create stiffened composite panel structures (referred to here as WrapToR Shells). A prototype WrapToR Shell unit cell is manufactured and tested under three-point bending, where it demonstrates high levels of specific stiffness and strength. This experimental result is benchmarked against idealised sandwich panels via a low fidelity comparative analysis, and the study shows that even a best-case sandwich panel of equivalent mass under a representative bending load has an 83% increase in displacement, highlighting the excellent stiffness truss reinforced panels can provide. The design space available to the truss reinforced panels is then explored using finite element analysis and a simple parameter sweep of key truss design variables. A Pareto frontier between the competing objectives of minimising mass and maximising rigidity is shown, and global trends in performance are highlighted. It is observed that increasing the size of the truss profile or longitudinal member has a near linear increase on EI/mass, whereas for increasing shear member angle the inverse is true. For increasing shear member diameter, a less obvious effect on EI/mass is seen, indicating a more complex relationship with the other design variables.

Design of metamaterial-based heat manipulators using isogeometric level-set topology optimization

We exploit level-set topology optimization to find the optimal material distribution for metamaterial-based heat manipulators. The level-set function, geometry, and solution field are parameterized using the Non-Uniform Rational B-Spline (NURBS) basis functions to take advantage of easy control of smoothness and continuity. In addition, NURBS approximations can produce conic geometries exactly and provide higher efficiency for higher-order elements. The values of the level-set function at the control points (called expansion coefficients) are utilized as design variables. For optimization, we use an advanced mathematical programming technique, Sequential Quadratic Programming. Taking into account a large number of design variables and the small number of constraints associated with our optimization problem, the adjoint method is utilized to calculate the required sensitivities with respect to the design variables. The efficiency and robustness of the proposed method are demonstrated by solving three numerical examples. We have also shown that the current method can handle different geometries and types of objective functions. In addition, regularization techniques such as Tikhonov regularization and volume regularization have been explored to reduce unnecessary complexity and increase the manufacturability of optimized topologies.

An Eigenfrequency-Constrained Topology Optimization Method with Design Variable Reduction

The dynamic response of structures heavily relies on eigenfrequency, so the optimization of eigenfrequency is valuable in various working conditions. The bi-directional evolutionary structural optimization (BESO) method has been widely applied due to its ability to eliminate grayscale elements. Based upon BESO, this paper introduces a topology optimization method that incorporates eigenfrequency constraints and reduces the number of design variables. In this method, the optimization objective was to minimize compliance. The Lagrange multiplier was used to introduce eigenfrequency constraints, allowing for coordinated control of compliance and eigenfrequency. To prevent oscillation during the optimization process, the sensitivity was normalized. Additionally, to achieve faster convergence, the variables were reduced after meeting volume constraints. The numerical examples demonstrate the effectiveness of this method in increasing the eigenfrequency of the structure and avoiding resonance.

Elevator block brake structural optimization design based on an approximate model.

An Aquila optimizer-back propagation (AO-BP) neural network was used to establish an approximate model of the relationship between the design variables and the optimization objective to improve elevator block brake capabilities and achieve a lightweight brake design. Subsequently, the constraint conditions and objective functions were determined. Moreover, the multi-objective genetic algorithm optimized the structural block brake design. Finally, the effectiveness of the optimization results was verified using simulation experiments. The results demonstrate that the maximum temperature of the optimized brake wheel during emergency braking was 222.09°C, which is 36.71°C lower than that of 258.8°C before optimization, with a change rate of 14.2%. The maximum equivalent stress after optimization was 246.89 MPa, 28.87 MPa lower than that of 275.66 MPa before optimization, with a change rate of 10.5%. In addition, the brake wheel mass was reduced from 58.85 kg to 52.40 kg, and the thermal fatigue life at the maximum equivalent stress increased from 64 times before optimization to 94 times after optimization.

Optimization design of shearer drum height adjusting mechanism based on particle swarm optimization algorithm

The underground working environment of the shearer is complex and the working conditions are relatively poor. It is necessary to continuously adjust the height of the rocker arm during the operation, improve the operation efficiency, and improve the ability of the shearer to adapt to the more complex coal seam working environment. In order to optimize the structure of the shearer adjustment mechanism, the strength and strength of the adjustment mechanism are improved by increasing the size and angle of the adjustment mechanism and reducing the size and angle. Therefore, an optimized particle group design method is proposed to optimize the drum adjustment mechanism of the shearer. Seven parameters such as large lever, small lever and maximum swing angle are selected as design variables. Under the condition of limiting mining height and rocker length, an optimization model with rolling angle and cylinder stress as objective functions is established. The working characteristics of each part of the coal machine height adjustment mechanism are analyzed. The particle swarm optimization algorithm is used to optimize the key parameters, and the optimization results are verified to ensure their accuracy. The optimization results are compared with the original parameters. The results show that compared with the pre-optimization, the cylinder stroke is shortened by 17.9%, the cylinder length is shortened by 8.94%, the rolling angle is reduced by 2.83%, the cylinder tension is reduced by 12.1%, and the rocker bending moment is increased by 6.83 %, which meets the original design goal. Therefore, the research provides a reference for the optimal design of the coal machine height adjustment system.

NETWORK DESIGN AND VEHICLE ROUTING PROBLEMS IN ROAD TRANSPORT SYSTEMS: INTEGRATING MODELS AND ALGORITHMS

In this paper, an integrated approach is proposed that incorporates the road network design problem and the vehicle routing problem, which are very often studied separately. This approach can be adopted when the routes to follow in a transport system have to be designed (e.g., for public transit with fixed and variable routes, or for freight distribution) jointly with the network topology and capacity. The goal is to minimise congestion and the impacts on the network from passengers and freight vehicles. The design (control) variables consist of the optimal vehicle routes and optimised road network; they are both discrete (link topology for passenger and freight, routes for passengers and freight vehicles, etc.) and continuous (link capacity in terms of reserved lanes, signal settings, etc.). The problem is modelled in congested transportation networks (e.g., in an urban centre). A heuristic algorithm is adopted to find the best network configuration and the best vehicle routes. The proposed model and the adopted algorithm are applied in a test system to analyse the limits of the methodology, to verify the advantage obtained from the joint method and its applicability. In the test system, the joint procedure gives good results in terms of cost decreases (from 25% to 31%). The reported methods can help public and private stakeholders in making decisions regarding transportation policy, especially in the urban environment.

Multi-physics and multi-objective optimization of a permanent magnet-assisted synchronous reluctance machine for traction applications

This contribution addresses the rotor design process of a Permanent Magnet-assisted Synchronous Reluctance Machine by adopting a multi-physics and multi-objective optimization algorithm. A Finite Element (FE) approach is employed to determine the electromagnetic and structural responses during the optimization. In particular, a detailed FE structural modeling is used, which often is based on simplifications and inaccuracies in the available literature. A genetic algorithm is adopted, with the objectives being the maximization of the mean torque, the minimization of the torque ripple and the minimization of the stress in the rotor. A parametric analysis of the geometric features precedes the optimization to establish the design variables which mostly affect the machine performance, and thus to reduce the computational cost of the optimization. The presented methodology consists of a useful tool for the final stages of the design process, and provides a rotor with a torque ripple reduced by 15.1% compared to an existing design used as a benchmark, while the mean torque and the maximum stress remain the same as the original configuration.

The Influence of Interior Design and Food Taste on Visitor Loyalty in Sunda Resto and Godong Ijo Pishing

This research aims to determine the influence of interior design and food taste on visitor loyalty at Sundanese Resto & Fishing Godong Ijo. The population of this study were all tourists who had visited the Sunda Resto & Fishing Godong Ijo with a sample of 120 people. This research uses primary data obtained through distributing questionnaires and interviews. The analysis technique used is the Partial Least Square (PLS) approach method which utilizes PLS-SEM or Structural Equation Modeling to measure and analyze the relationship between variables. From data processing using SmartPLS 4, Interior Design variables influence Customer Loyalty and the Food Taste variable influences Customer Loyalty.

Friction Stirs Processing - State of The Art Process to Fabricate Metal Matrix Composites

Friction stir processing(FSP) is the solid state method to fabricate the surface metal matrix composites(MMC). This process has been derived from the concept of Friction stir welding. As this process is performed in solid state, many defects related to phase transformation can be avoided. As this process is done below the melting point temperature of metal or alloy, it is easier to control the process. Machine variables (tool rotational speed, tool traverse speed, tool tilt angle etc.), tool design variables (diameter, profile and height of probe and shoulder of the FSP tool), and material properties are the main process variables to perform FSP in order to fabricate Metal matrix composite. In addition to these variables number of passes, tool traverse patterns, reinforcement particles’ content and its’ types also can be considered as process variables. Tribological properties’ comparison can be done between alloy and MMC fabricated by FSP for different combinations of process parameters. Microstructural study also can be carried out in order to see the effects of above process parameters. In this paper the above aspects are summarized and performance assessment done by various researchers has been covered.

Analysis of safe and effective next-generation rail signalling systems

Moving Block (MB) and Virtual Coupling (VC) rail signalling will change current train operation paradigm by migrating vital equipment from trackside to onboard to reduce train separation and maintenance costs. Their actual deployment is however constrained by the industry’s need to identify configurations of MB and VC signalling equipment which can effectively guarantee safe train movements even under degraded operational conditions involving component faults. In this paper, we analyse the effectivity of MB and VC in safely supervising train separation under nominal and degraded conditions by using an innovative approach which combines Fault Tree Analysis (FTA) and Stochastic Activity Networks (SAN). An FTA model of unsafe train movement is defined for both MB and VC capturing functional interactions and cause-effect relations among the different signalling components. The FTA is used as a basis to apportion signalling component failure rates needed to feed the SAN model. Effective MB and VC train supervision is analysed by means of SAN-based simulations in the specific scenario of an error in the Train Position Report (TPR) for five rail market segments featuring different traffic characteristics, namely high-speed, mainline, regional, urban and freight. Results show that the thresholds of the design variables depend on the considered signalling system alternative and the investigated market segment. In particular, the TPR delay threshold allowed for MB is higher than for VC. This means that to ensure a safe train movement, VC cannot absorb a TPR delay of longer than 1.5 s, which corresponds to the mainline market segment. For MB instead, the results show that the maximum TPR delay can reach 3.9 s for high-speed and freight railways. In addition, results showed that the integration of an FTA in a SAN model can provide a better understanding of the safety-performance behaviour of a system where VC showed a higher number of braking indications with respect to MB for the same TPR error failure rate. This means that for VC to effectively supervise the train separation at the same safety level as MB, we would need to have a much higher reliability of the TPR. The overall approach can support infrastructure managers, railway undertakings, and rail signalling suppliers in investigating the effectiveness of MB and VC to safely supervise train movements in scenarios involving different types of degraded conditions and failure events. The proposed method can hence support the railway industry in identifying effective and safe design configurations of next-generation rail signalling systems.

Stiffness-driven design and optimization of a 3D-printed composite prosthetic foot: A beam finite Element-Based framework

Composite foot prostheses are traditionally produced via lamination, a process that grants high structural efficiency. However, it is an expensive and time-consuming process. Production rate and customizability are thus limited. Additive manufacturing of composites can be a potential solution to these limitations. This work presents a tool to design and optimize Continuous Fiber-Reinforced Additively Manufactured (CFRAM) prosthetic feet using beam Finite Element (FE) modeling. This optimization tool was developed for weight minimization and obtaining a CFRAM prosthesis design matching up to three static stiffness parameters. The design variables were defined through parametrizing the geometry of the prosthesis designed and using the composite structure parameters. Thanks to the versatility of the tool, solutions to multiple optimization and design cases were used to assess different design concepts, such as the shape of the prosthesis (C-shape or J-shape). Also, the tool successfully duplicated the stiffness characteristics of an assumed laminated prosthesis. Finally, the sources of inaccuracy associated with the beam FE modeling approach were identified through a comparison with plane stress FE analysis.

Research on the Influence of Humidity on the Manufacture of GFRP Vessels in the Equatorial

The objective of this research work is to analyze the behavior between fiberglass laminate under tensile tests, assembled under different humidity conditions. For which specimens were designed under the regime of the international standard ASTM D3039; which took an assembly process within a controlled environment; the design variables used were relative humidity and curing time. Subsequently, the traction-displacement behavior was checked under a uniaxial force, obtaining the maximum take-off force. In addition, Simpson numerical integration was applied to calculate elastic energy. Obtaining that the relative humidity and the days of curing influence the chemical and mechanical properties of the material. Se shows that the percentage of humidity recommended for assembling laminates in GRP is 66% since it has greater elastic energy and take-off force. Finally, it is concluded that to have a high resistance in the material at least 7 days of curing of the epoxy resin must be applied.