Design Parameters Research Articles

Probabilistic design and optimization of thermal protection system with variable thickness based on non-uniform aerodynamic heating

Thermal Protection System (TPS) is a critical component of space vehicles to protect them from damage by extreme aerothermal heating conditions. The uncertainty of the aerothermal heating conditions, including approaching velocities, atmospheric density, pressure, etc., significantly affects the aerothermal heating imposed on the TPS, vastly changing the initial design conditions. In this study, we developed a new uncertainty quantitative (UQ) analysis method to comprehensively consider all the uncertainty of TPS materials, structures, and aerothermal heating conditions. To address the challenges of a massive amount of input and determined optimization parameters, we first induced the response surface method and Monte Carlo algorithm to produce a large number of analysis samples for Probabilistic Design. Then, the key affecting factors, not all the input design parameters, were chosen for optimization with sequential optimization and reliability assessment (SORA) strategy by a sensitivity analysis. With such improvements, the optimization for UQ analysis becomes practical. We used this new UQ method to analyze the effects of uncertainty of the aerothermal heating conditions on the thermal protection layer. A variable thickness design is proposed to adapt the non-uniform aerothermal heating conditions for the TPS. The results show that significant light-weighting can be achieved without the reliability penalty. The optimized structure also reduces internal temperature gradients and facilitates a more uniform temperature field distribution for the TPS. This study provides a new UQ engineering design approach for the system with many designed parameters.

Cyclic performance of RC frame joints with drilled openings

The construction industry commonly employs reinforced concrete (RC) beams with utility pipe openings to facilitate the passage of pipes through structures. These openings can be made through pre-construction or post-construction processes. Pre-construction openings in RC members are included in the design, and in most cases, designers include reinforcements around the opening to deal with the stress concentration and failure mechanism caused by the presence of the opening. However, post-construction or drilled openings are added after the structure is built, potentially disrupting established load paths, and developing stress concentrations that are not anticipated by the designer. In this study, three-dimensional nonlinear numerical finite element models (FEM) models were developed and validated according to four sets of experimental data. These models formed the basis for a parametric study exploring different design parameters. Parameters such as the width and depth of the specimen and the size of the opening were investigated. The results suggest that the presence of the opening leads to a brittle behavior and a sudden drop in the strength and stiffness of the specimen after the ultimate load. Increasing the depth of the beam results in more brittle behavior in specimens with openings and decreased the drift ratio where the specimen failed by up to 75%. However, increasing the width of the specimen increases the ductility of these specimens. Finally, opening size was found to lead the specimen to behave more brittle in all cases, and decrease the maximum drift ratio from 5% to 1.5%, and decrease the load capacity in 1.5% drift ratio by up to 61%. This study will help engineers and designers to understand the effect of beam-column joints with post-construction openings under cyclic loading, whether these openings are intentional or by human error.

A penta-linear backbone model for unbonded post-tensioned concrete masonry shear walls

Unbonded post-tensioned concrete masonry (UPCM) shear walls are an effective seismic force resisting system due to their ability to mitigate expected damage through their self-centering capabilities. A few design procedures were proposed to predict the in-plane flexural response of UPCM walls, albeit following only basic mechanics and/or extensive iterative methods. Such procedures, however, may not be capable of capturing the complex nonlinear relationships between different parameters that affect UPCM walls’ behavior or are tedious to be adopted for design practice. In addition, the limited datasets used to validate these procedures may cast doubt on their accuracy and validity for new, unseen data, further hindering their adoption by practitioners and design standards. To address these issues, an experimentally-validated nonlinear numerical model was adopted in this study and subsequently employed to simulate 95 UPCM walls with different design parameters to compensate for the lack of relevant experimental data in the current literature. Guided by mechanics and using this database, an evolutionary algorithm, multigene genetic programming (MGGP), was adopted to uncover the relationships controlling the response of UPCM walls, and subsequently develop simplified closed-form wall behavior prediction expressions. Specifically, through integrating MGGP and basic mechanics, a penta-linear backbone model was developed to predict the load-displacement backbone for UPCM walls up to 20% strength degradation. Compared to existing predictive procedures, the prediction accuracy of the developed model and its closed-form nature are expected to facilitate better understanding of such wall behaviors and subsequently open the gate to further incorporate other experimental and numerical results to ultimately incorporate UPCM in mainstream designs in the near future.

Incorporating Season and Solar Specificity Into Renderings Made by a NeRF Architecture Using Satellite Images.

As a result of Shadow NeRF and Sat-NeRF, it is possible to take the solar angle into account in a NeRF-based framework for rendering a scene from a novel viewpoint using satellite images for training. Our work extends those contributions and shows how one can make the renderings season-specific. Our main challenge was creating a Neural Radiance Field (NeRF) that could render seasonal features independently of viewing angle and solar angle while still being able to render shadows. We teach our network to render seasonal features by introducing one more input variable - time of the year. However, the small training datasets typical of satellite imagery can introduce ambiguities in cases where shadows are present in the same location for every image of a particular season. We add additional terms to the loss function to discourage the network from using seasonal features for accounting for shadows. We show the performance of our network on eight Areas of Interest containing images captured by the Maxar WorldView-3 satellite. This evaluation includes tests measuring the ability of our framework to accurately render novel views, generate height maps, predict shadows, and specify seasonal features independently from shadows. Our ablation studies justify the choices made for network design parameters.

Optimizing MEP Design in Pharmaceutical Cleanroom with the Integration of 2D To 7D in BIM

Abstract: This paper examines the optimization of pharmaceutical cleanroom design using 2D to 7D Modelling in Building Information Modelling (BIM). The goal is to enhance the reliability, different methods, statistical data, and performance of pharmaceutical production plants by effectively allocating components within design constraints. Mathematical optimization techniques improve facility design, ensuring robustness and operational efficiency. The study proposes a reliable optimal design for air-conditioning systems in pharmaceutical cleanrooms, considering uncertainties in design parameters and operational strategies. Resilient cleanroom systems are developed, and adaptable to various conditions while maintaining high performance standards. Additionally, the research explores the application of experimental design methodologies in optimizing drug delivery systems, such as factorial and etc, to enhance the quality and efficiency of pharmaceutical products and processes.

Performance Enhancement in Submersible Pump Impellers: Design and Optimization Approaches

Abstract: Submersible pumps are essential components in various industries, including water supply, wastewater management, and oil extraction. Their efficiency and reliability are crucial for ensuring consistent fluid transport. At the core of submersible pumps lies the impeller, which directly influences pump performance. This paper examines advanced design and optimization approaches to enhance the performance of submersible pump impellers. By analyzing key factors such as blade geometry, material selection, and impeller design parameters, we explore methods to improve hydraulic performance, energy efficiency, and operational stability. Experimental validation confirms the effectiveness of these approaches in achieving superior pump efficiency and longevity. This study contributes to the advancement of submersible pump technology and sets a foundation for future research in the field.

Performance Variation by Design Parameters of Submerged Inlet in Transonic Flow

Performance Variation by Design Parameters of Submerged Inlet in Transonic Flow

Challenges of Undular Jump Modelling

The study of open channel flow hydraulics extends beyond supercritical and subcritical flow states to include a distinct state known as near-critical flows. This category encompasses various hydraulic phenomena, with some of the most notable being solitary waves, cnoidal waves, and undular jumps. This paper specifically addresses the phenomenon of undular jumps, providing a brief overview of its characteristics and discussing instances of undular jump formation in natural rivers settings and during the operation of various hydraulic structures. When there is a sudden change in flow depth from a lower level to a higher one, it typically leads to a sudden increase in the water surface, known as a hydraulic jump. However, if the jump is relatively small, meaning the depth change is minor, the water does not rise noticeably and abruptly. Instead, it will traverse from the lower to the higher stage through a sequence of gradually diminishing undulations that extend over a considerable distance. Such phenomenon is called an undular jump.The occurrence of undular hydraulic jumps can be observed in various open channels such as irrigation and water supply channels, beneath vertical sluice gates, within estuaries during specific tide periods, and in narrow or shallow passages affected by strong currents. Additionally, this phenomenon often manifests downstream of low drop structures or in transitional zones from steep to gently sloping channels. In channels where undular jumps occur, waves with significant amplitudes develop and travel downstream of the jump. Accounting for the propagation of these downstream free-surface waves is essential for canal design and natural channel maintenance. The wave height serves as a crucial design parameter that dictates the necessary sidewall height of the canal. In natural channels, the embankment height must exceed the crest of the free-surface undulations to prevent overtopping and subsequent erosion, which could ultimately lead to bank destruction. Moreover, the propagation of free-surface waves may subject downstream canal structures, such as gates, locks, and weirs, to additional impact loads, perturbations, and vibrations.In recent years, different scientists have made various attempts to investigate and describe this phenomenon using physical, mathematical and computer modelling. However, this phenomenon has a number of peculiarities that are not always taken into account. An objective of this article is to present the particularities of different type of undular jump modelling and to compare the obtain results.

Nonlinear vibration analysis of thin plate with periodically distributed tunable-stiffness nonlinear oscillators in subsonic flow

This paper provides a new passive control method for nonlinear vibration of subsonic thin plates. The control method uses periodically distributed tunable-stiffness nonlinear oscillators (NLO). By using von Karman’s nonlinear plate theory and subsonic aerodynamic model, the nonlinear dynamic model of thin plate is established based on Hamilton’s principle. Through analyzing the system’s nonlinear dynamics bifurcation, the impact of periodic distribution on the stability is discussed. The amplitude-frequency responses are discussed under different NLO installation modes and design parameters by using Matcont software. The results show that the periodically distributed tunable-stiffness nonlinear oscillators can improve the stability of the system and have a remarkable suppression effect. The optimal control scheme for vibration suppression by periodically distributed tunable-stiffness nonlinear oscillators is obtained. The results obtained from this research can offer a valuable understanding of nonlinear vibration control, thereby enabling the identification of various control approaches that can be implemented in practical applications during future design endeavors.

Transient forward harmonic adjoint sensitivity analysis

AbstractThis paper presents a transient forward harmonic adjoint sensitivity analysis (TFHA), which is a combination of a transient forward circuit analysis with a harmonic balance-based adjoint sensitivity analysis. TFHA provides sensitivities of quantities of interest from time-periodic problems with many design parameters, as used in the design process of power-electronics devices. The TFHA shows advantages in applications where the harmonic balance-based adjoint sensitivity analysis or finite difference approaches for sensitivity analysis perform poorly. In contrast to existing methods, the TFHA can be used in combination with arbitrary forward solvers, i.e., general transient solvers.

Optimizing the Shape of the Spinning Electrode for Needleless Coaxial Electrospinning

This work deals with designing the optimal shape of the spinning electrode to optimize the distribution of the electric field and suppress the formation of corona discharges on the surface of the electrode during electrospinning using direct current (DC). Some of the solutions used for electrospinning are solved in flammable solvents, such as PVB; therefore, corona discharges are hazardous, as they cause sparks that can cause fires and explosions. The shape optimization was carried out on a plate weir electrode, which uses the principle of free surface spinning. Using the electric field simulation, an analysis of the plate weir spinner was carried out, and its optimization was aimed at minimizing the occurrence of corona discharges, which negatively affect the spinning process. Based on the simulations’ results, the spinning electrode design parameters were adjusted so that an even distribution of the electric field over the entire active surface of the electrode was ensured, and the incidence of corona discharges was prevented. A laboratory experiment was used to validate the function of the design changes in the spinning electrode.

Aerodynamic modeling and performance analysis of model predictive controller for fixed wing vertical takeoff and landing unmanned aerial vehicle

This research focuses mainly on the aerodynamic modelling and performance analysis of a model predictive controller for a hybrid fixed-wing vertical takeoff and landing of unmanned aerial vehicle. The aerodynamics, which comprises several aerodynamic characteristics including the lift, drag, and thrust coefficients, is modelled using Newton’s second law of motion. The force and moment equations were obtained, and they were then converted into matrix and state equation form, together with the transformation matrices. The essential equations with six degrees of freedom (6 DoF) and 12 state matrices including the control input and manipulating variables were obtained. The proposed model predictive controller (MPC) was designed using the optimal model predictive controller design parameters, such as a sampling time of 0.1, a prediction horizon of 15, a control horizon of 3 and additional controller settings. With a settling period of 3 s, an overshoot of 0.5865, and a steady state inaccuracy of 0.00785, the MATLAB simulation demonstrates that the system variables, including roll, pitch, and yaw, are stabilized. This MPC control is more effective in anticipating and optimizing the UAV than other control strategies. Eventually, the controller’s simulation on MATLAB Simulink demonstrates the controller’s ability to stabilize and control the system in a real-time application. Autonomous vertical takeoff and landing operations depend heavily on the mathematical model and architecture of the flight controller. Among the uses are inspection, monitoring, and rescue.

Numerical and artificial neural network analysis of tunnel liner design parameters – a comparative study

ABSTRACT This paper proposes the development of an analytical-based Artificial Neural Network (ANN) model for predicting the concrete segmental lining parameters and comparing it with the finite element method, Rocscience tool. To achieve this aim, the dataset was prepared for twelve different loading conditions using the analytical equations by Muir Wood and Curtis. Using this dataset, an ANN model was developed for predicting the segmental lining parameters, viz. displacement, bending moment, axial and shear force. Furthermore, the Rocscience tool was used to analyse the aforementioned design parameters, and the results of these two methods were compared and summarised. It is found that the developed ANN model shows reasonable results of liner design parameters with the Rocscience program. The efficiency of both techniques was evaluated using the statistical measures viz. Mean Absolute Error, Root Mean Square Error, and Coefficient of Efficiency. It is observed that the ANN model is best fitted for the prediction of liner shear and axial force, while it could not find the optimised solution for liner displacement and bending moment. The finding of this study showed that the developed ANN model can be applied to predict the tunnel liner design parameters instead of the alternative complicated and time-consuming techniques.

Experimental investigation of warpage in thin CF/PEKK composite laminates consolidated under non-isothermal conditions

In this study, we investigated the effect of several processing conditions on warpage in carbon-fibre/PEKK composites manufactured under non-isothermal conditions. A multi-level factorial design of experiments was employed to study the effect of process and design parameters on warpage. Analysis-of-variance was used to establish the significance of the main factors as contributors to warpage. The number of plies and consolidation pressure were the factors that contributed significantly to warpage. A regression model was used to predict the warpage of panels consolidated using aluminium tooling, giving a reasonably good prediction of less than 18% difference. A panel with variable thickness was also manufactured, based on the prior observations, pressure and lay-up configurations were successfully altered to reduce warpage. DSC results showed that the warpage of semi-crystalline PEKK composites consolidated under non-isothermal conditions is a result of a differential in shrinkage across the laminate, as the degree of crystallinity varied with temperature and consolidation pressure.

Combating contamination and contagion: Embodied and environmental metaphors of misinformation

In recent years, government agencies, information institutions, educators and researchers have paid increasing attention to issues of misinformation, disinformation and conspiracy theorizing. This has prompted a seemingly endless supply of guides, frameworks and approaches to ‘combating’ the problem. In studies of mis- and disinformation, a constellation of analogous concepts are defined in multiple ways across multidisciplinary literatures and institutional contexts. Misinformation, disinformation and conspiracy theory are often conflated, lacking specific, portable definitions across fields of study. Linguistic metaphors are often leveraged in place of this definitional work. The larger conceptual metaphors that they connote contain normative assumptions that often impose values and moral imperatives, imply deficiencies, assume intent, and foreground individual agency or lack thereof. Metaphors are as restrictive as they are illuminating; once used, a metaphor also applies constraints to the way in which a phenomenon can be understood. Metaphors not only shape the ways in which science is communicated to the public, but also the kinds of questions that are asked, the theories and methods used, and the parameters of the research design. By analyzing instances of linguistic metaphor, this exploratory study identifies and develops two conceptual metaphors that are frequently evoked to discuss mis- and disinformation: embodied health metaphors and environmental health metaphors. The former includes linguistic metaphors like viral/virality, infodemic, infobesity, information hygiene, information dysfunction, and information pathology. The latter includes linguistic metaphors like information pollution, infollution, and digital wildfires. Uncritically invoking such metaphors adopts tacit arguments deriving from the original field of study (e.g., public health’s tendency to equate individual embodied health with virtue), or the image of the metaphor itself ( digital wildfires implies quick spread and immediate danger), or both. Widespread and uncritical use of such metaphors, we argue, rewards speed and epistemic homogeneity in mis- and disinformation research – ultimately discouraging in-depth inquiry.

Innovative claw rotor design for claw vacuum pump and its power consumption analysis

The claw vacuum pump is extensively utilized in semiconductor, photovoltaic and aerospace industries because of its dry oil-free and compact structure. In order to reduce the power consumption of the claw vacuum pump caused by its special mixing process during operation, a novel pair of claw rotors was proposed. This innovation involves replacing the conventional circular arc at the dedendum of the claw rotors with an eccentric circular arc. A geometric model of the novel claw rotor was established, and the geometric characteristics of both the novel and conventional claw rotors were compared. Subsequently, the optimal design parameters were determined. The pressure distribution and power consumption of two claw vacuum pumps were analyzed with numerical simulations. Study results indicates that the power consumption of the proposed claw vacuum pump in the mixing process is reduced by 72.3 %, and the total power consumption is reduced by 12.6 % compared to the conventional pump. The study is of great significance for reducing power consumption of the claw vacuum pumps and improving application.

Seismic performance of HECC/RC beam–column external joint with no stirrup and reduced anchorage length in core region

In this paper, steel–polyethylene hybrid fiber-reinforced strain-hardening cementitious composites (HECC) are applied in beam–column external joint core region to form a novel HECC/reinforced concrete (RC) composite beam–column joint with reduced anchorage length of beam longitudinal rebar and eliminated transverse rebar, and thus to alleviate rebar congestion and simplify the construction process efficiently especially for precast RC frame structures. Five external beam–column joint specimens are constructed and tested under cyclic loading to illustrate the influences of the anchorage length of beam longitudinal rebar and longitudinal rebar ratio on the seismic performance of beam–column joint. The effects of design parameters on seismic performance, including hysteresis behavior, degradation of strength, energy dissipation capacity, and cracking patterns are discussed in detail. Experimental results indicate that the replacement of normal concrete with HECC in beam–column joint core region could apparently reduce the amount of stirrups in the joint core area while maintaining reliable seismic behavior. Remarkably, specimen with no stirrups in the core area exhibits nearly equivalent seismic behavior to that of the control RC specimen. Furthermore, the application of HECC in joint core area allows for a substantial reduction of the required anchorage length for the beam longitudinal rebar to 9d, which further simplifies the construction process considerably.

Study on the Two-Step Construction Method of Super Large Cross-Section Tunnels Crossing Karst Cave Areas

To explore the solution of the two-step method applied in the rapid construction of super large cross-section tunnels passing through IV-and V-grade surrounding rock sections in karst cave areas, based on an engineering example of the Lianhuashan Tunnel, we use the numerical calculation method to analyze the stability of surrounding rock and the design parameters of the control measures for super large cross-section tunnels during the construction of the step method. The calculated results show that the working face of IV-grade surrounding rock can be stabilized by an advanced small pipe, and the stability of the supporting structure should be controlled mainly by IV-grade surrounding rock. In order to control the stability of the tunnel face, it is necessary to use an advanced large pipe shed in the surrounding V-grade rock. The reinforcement range of the advanced large pipe shed is 120° and the length is 20 m. This is the most economical design parameter of the advanced large pipe shed, ensuring the deformation control effect. For control of the stability of the supporting structure, under the condition that the working space is suitable for large machinery, the settlement of the arch of the supporting structure can be obviously reduced by shortening the step cycle footage and reducing the step length, and the peripheral convergence of the supporting structure can be obviously reduced by reducing the step height. After comprehensive analysis and considering the development of karst caves, the advanced support measures, design parameters, bench excavation design parameters, initial support measures, karst cave treatment measures, and bench construction process of IV- and V-grade surrounding rock is determined. The application verification shows that the research results have a good control effect on the stability of the surrounding rock and cave and are suitable for large-scale mechanical operations, which can significantly improve the excavation speed of the super large cross-section tunnel passing through the IV- and V-grade surrounding rock sections in the karst cave area.

An automatic completion method for design domain knowledge graph using surrogate model, for rapid performance evaluation

The data and information generated during the design process, such as part parameters, affect the efficiency and quality of product design. Knowledge graph (KG) is often used to express and reuse the above knowledge. However, due to the decentralised and complex nature of the KG, it lacks the quantitative knowledge required for part selection, e.g. the relationship between part type and performance. To complete the knowledge and meet the requirements for rapid and accurate performance evaluation, this paper proposes an automatic KGC method based on a surrogate model. Firstly, the schema layer is established based on the design knowledge ontology. For the sampling process, the query statement is applied to extract knowledge such as design parameters, which define the range of sample points. Secondly, the design of experiments (DOE) method can obtain the data set of the target performance through simulation. Surrogate models are built based on multiple machine learning algorithms. Meanwhile, the hyperparameter optimisation method can further improve the prediction accuracy of the model. Finally, the performance of the design scheme is predicted, and the results are used to complete the KG through knowledge extraction. The method is validated by the selection and evaluation of bogie parts.

Application of a Multi-Criterion Decision-Making Method for Solving the Multi-Objective Optimization of a Two-Stage Helical Gearbox

This paper provides a novel application of a multi-criterion decision-making (MCDM) method to the multi-objective optimization problem of designing a two-stage helical gearbox. This study’s goal is to identify the ideal primary design elements that increase gearbox efficiency while reducing the gearbox cross-section area. In this work, three primary design parameters were selected for investigation: the gear ratio of the first stage and the coefficients of wheel face width (CWFW) of the first and second stages. The multi-objective optimization problem was further split into two phases: phase 1 solved the single-objective optimization problem of minimizing the gap between the variable levels, and phase 2 solved the multi-objective optimization issue of identifying the ideal key design factors. Moreover, the multi-objective optimization problem was handled by the SAW method as an MCDM approach, and the weight criteria were computed using the entropy approach. This study’s significant characteristics are as follows: First, a multi-objective optimization problem was successfully solved using the MCDM approach (SAW technique) for the first time. Second, the power losses in idle motion were investigated in this work in order to determine the efficiency of a two-stage helical gearbox. From this study’s findings, the ideal values for three major design parameters can be determined for the design of a two-stage helical gearbox.