Engineering Design Research Articles

Design and Optimization of LPG Safety Cap using Finite Element Method

This paper presents a comprehensive study on the design and optimization of LPG safety caps, aimed at enhancing safety, reducing material consumption, and optimizing performance. The project employs SolidWorks simulation tools to conduct research and concept design phases. The primary objective is to ensure product safety while minimizing costs through Finite Element Analysis (FEA). The final product undergoes rigorous evaluation for performance and consumer safety. Three main goals guide this investigation: to scrutinize existing LPG safety cap designs, minimize material usage, and simulate the optimal design for enhanced safety. Analysis of the current design reveals vulnerabilities, including theft of LPG gas from sealed cylinders and escalating HDPE prices. Proposed designs simplify the current model and economize material consumption, successfully addressing the second objective. Through simulation, an optimal design (Design 8) emerges with superior characteristics compared to the existing model. Design 8 demonstrates a reduced total weight, higher safety factor, and lower maximum von Mises stress value. Notably, it exhibits enhanced safety and resilience, mitigating failure risks under stress conditions. The findings highlight the potential for creating stronger and safer designs while minimizing material requirements. In conclusion, Design 8 emerges as a superior alternative to the current design, boasting advantages in weight reduction, stress tolerance, safety factor, and optimization potential. This study underscores the significance of utilizing advanced computational methods to refine engineering designs for improved safety and efficiency in LPG safety caps.

Features of construction at low temperatures

The present paper considers the features of construction at low temperatures and introduces the previous studies on improving the reliability of metal and reinforced concrete structures. Low temperatures adversely affect penetration of the edges of metal products during welding. Notably, design engineers consider the results of investigations and calculations, and incorporate steel products made of lowalloy, stainless steels, and nickel alloys. These materials demonstrate high viscosity, good weldability, retain strength in the process of manufacturing structures and their operation. The paper analyzes the construction works in winter conditions and considers installation as one of the main technological processes in construction. In addition, the paper lists the restrictions for welding and concreting, as well as indicates the conditions for structures to be installed using bolts or manual arc welding. Manufacturing plants are known to treat metal products and structures with protective coatings prior to transportation to the construction site. These technological operations are aimed at protecting metal from corrosion and at retaining heat within buildings. All winter concreting techniques are indicated to be implemented on the construction site at temperatures below 5°C. Gaining the required strength of the cement needs more time in cold temperatures than at a temperature of +20°C. The method of artificial heating, presented in the paper, is intended to create durable concrete and reinforced concrete products and structures.

MVSF-AB: Accurate antibody-antigen binding affinity prediction via multi-view sequence feature learning.

Predicting the binding affinity between antigens and antibodies accurately is crucial for assessing therapeutic antibody effectiveness and enhancing antibody engineering and vaccine design. Traditional machine learning methods have been widely used for this purpose, relying on interfacial amino acids' structural information. Nevertheless, due to technological limitations and high costs of acquiring structural data, the structures of most antigens and antibodies are unknown, and sequence-based methods have gained attention. Existing sequence-based approaches designed for protein-protein affinity prediction exhibit a significant drop in performance when applied directly to antibody-antigen affinity prediction due to imbalanced training data and lacking design in the model framework specifically for antibody-antigen, hindering the learning of key features of antibodies and antigens. Therefore, we propose MVSF-AB, a Multi-View Sequence Feature learning for accurate Antibody-antigen Binding affinity prediction. MVSF-AB designs a multi-view method that fuses semantic features and residue features to fully utilize the sequence information of antibody-antigen and predicts the binding affinity. Experimental results demonstrate that MVSF-AB outperforms existing approaches in predicting unobserved natural antibody-antigen affinity and maintains its effectiveness when faced with mutant strains of antibodies. Datasets we used and source code are available on our public GitHub repository https://github.com/TAI-Medical-Lab/MVSF-AB.

Laser Construction TiOx-Ag heterostructure interface for high sensitive coupling resonance enhanced fluorescence in bacterial nucleic acid amplification sensor chip

Coupled resonance at the noble metals and metal oxides heterogeneous interface can enhance the fluorescence of molecules. This fascinating direction provides high value for the preparation and engineering design of fluorescence sensing platforms in nucleic acid sensing, pathogen detection and biological imaging. Here, an integrated nucleic acid amplification sensor chip consists of an array of silver nanoparticles/oxygen vacancy titanium oxide (TiOx-Ag) heterostructure substrates. The femA gene of Staphylococcus aureus was amplified and detected by enhancement fluorescence on the integrated chip. The TiOx-Ag heterostructure array was prepared by a laser method, the enhanced fluorescence performance was investigated in detail using calcein as a probe. The optical, electronic structure and plasmonic local field analysis indicate the strong coupling between the fluorescence molecule and the TiOx-Ag crystal plane, which inspired the excellent fluorescence signal of calcein, with an enhancement factor of up to 5. Staphylococcus aureus was detected by the above chip with a detection limit as low as 157 cfu/mL. These methods were applied to the detection of spiked serum samples with good detected performances, providing a powerful tool for rapid and reliable diagnosis of pathogens in medical institutions.

Carbon matrix NiFeP/C nanoparticles anchored on Ti3C2Tx nanosheets as heterostructure high-performance anode for lithium-ion batteries

Engineered micro-nano heterogeneous architectures for transition metal phosphide (TMPs) anode materials in lithium-ion batteries (LIBs) provide multifunctional active components. These components synergistically interact to address pivotal challenges of pronounced volume expansion and sluggish reaction kinetics within the electrode. Consequently, this engineering design approach significantly enhances the overall battery performance. In this study, a self-assembled approach is employed to integrate hybridized NiFe-PBA nanocubes with two-dimensional (2D) monolayer MXene (Ti3C2Tx), producing a heterostructured NiFeP/C@Ti3C2Tx composite. In this meticulously engineered architecture, the interface between the outer MXene layer and NiFeP embedded within the carbon matrix exhibits several distinct superiorities, such as rapid interfacial ion migration, multidirectional migration pathways, and strong spatial adaptability. The resulting non-uniform phase structure effectively mitigates electrode expansion and enhances electronic conductivity. Consequently, the NiFeP/C@Ti3C2Tx-15 composite demonstrates distinct performance advantages over NiFeP/C without MXene. The composite achieves a specific capacity of 689.4 mAh g⁻¹ at 200 mA g⁻¹ over 300 cycles, double that of NiFeP/C. Furthermore, density functional theory (DFT) calculations validate the electronic conductivity facilitated by the heterointerface between MXene and NiFeP, substantiating the strategic significance of the heterostructure in advancing high-performance anode materials for lithium-ion batteries.

Two-group interfacial area concentration model for dispersed gas-liquid flows in large-diameter pipes

Interfacial area concentration (IAC) plays a critical role in heat and mass transfers between gas and liquid phases through the interfaces. As interfacial area increases, mass and heat transfers between phases increase. Hence, a reliable IAC estimation is important for two-phase flow numerical simulations to conduct engineering designs and safety analyses. Gas bubbles show different behavior according to their shapes and sizes. Based on the size, gas bubbles can be classified into two groups that show different characteristics, such as IAC. Hence, two-group modeling helps to achieve a general approach for estimating the IAC in bubbly to beyond-bubbly flow regimes. Available models in the literature use empirical correlations to obtain group one and group two void fractions. These empirical approaches are not reliable for different flow conditions. In addition, these models are usually complex with several empirical constants. This study aims to develop a two-group area-averaged IAC model for upward vertical dispersed flows through large-diameter pipes. In addition, this study proposes using a general approach based on the two-group drift-flux model to calculate two-group void fractions rather than applying empirical correlations. The models are evaluated using 156 two-group measured data points in dispersed flow conditions through large-diameter pipes. The resulting prediction errors for group one and group two IAC models are 24.1 % and 34.2 %, and the errors for group one and group two void fraction predictions are 22.8 % and 25.6 %, respectively.

Machine learning techniques for predicting the peak response of reinforced concrete beam subjected to impact loading

To meet the growing need for resilient structures in seismic and high-impact zones, accurate prediction of the response of reinforced concrete (RC) beams under impact loads is essential. Traditional methods, such as experimental testing and high fidelity finite element models, are often time consuming and resource intensive. To address these challenges, this study investigates various ensemble and non-ensemble machine learning techniques—including support vector machine, gaussian process regression (GPR), k-nearest neighbor (KNN), gene expression programming, random forest, decision tree, boosted tree, adaptive boosting tree, gradient boosting algorithm, stochastic gradient descent, and artificial neural network—for predicting the peak response of RC beams under impact loads. A set of 145 experimental data points from 12 different sources is used to train and evaluate these machine learning models. Key parameters in the data include beam width and depth, span, reinforcement ratios, concrete strength, steel yield strength, deflection, and impact characteristics. Except for KNN, all models showed satisfactory generalization capabilities with R2 values over 0.8. Statistical errors such as RMSE, a-10 index, MAE, and a-20 index are within acceptable limits. The GPR model is the most effective with R2 value of 0.95. Moreover, Shapely analysis identified beam depth, impact velocity, and beam breadth as critical factors. Overall, this study demonstrates the efficacy of machine learning in accurately predicting the behavior of RC structures under impact loads, providing valuable tools for civil engineers in design and analysis.

Urban design and wildfire engineering at the wildland-urban interface: a review of international urban planning and building requirements

It has been almost a decade since Gonzalez-Mathiesen and March (2014) completed their international analysis that identified 9 design features for wildfire risk reduction via urban planning. Despite their recommendations and subsequent global attempts to enhance and improve resilience from an urban design perspective, wildfires1 remain one of the costliest hazards globally, both from a financial and a human perspective. This continued devastation raises the question as to whether urban design and wildfire engineering practices have either been adopted or changed since Gonzalez-Mathiesen and March (2014). To consider this, this paper presents a review and comparison of contemporary international wildland-urban-interface-related urban design legislation, policy and frameworks. Inconsistent approaches to addressing wildfire-related risk, and at times competing standards required between planning and building approaches were identified. These only serve to further reduce the potential effectiveness of measures intended to improve wildfire resilience at the national and international scales. Future work should focus on establishing evidence-based performance standards that emphasise the practical application of the findings of the best available current research to be incorporated into planning and construction. At the same time, it may be necessary to review policy approaches to clearly align key definitions of tolerable risk as well as provide clarification about how performance standards can be demonstrated.

Matching analysis between the heating/cooling capacity of PVT heat pumps and the heating/cooling demand of residential buildings across various regions in China

PVT-HP (Photovoltaic-Thermal Heat Pump) is a novel type of energy saving technology. Existing researches on PVT-HP technology focuses only on its operating performance under some specific conditions, ignoring the matching of its energy supply capacity with the energy demand of buildings, which is very important for its engineering design and application. In this paper, the matching relationship between the heating/cooling capacity of the PVT-HP system and the heating/cooling demand of residential buildings in major cities of China has been analyzed. To achieve this goal, a novel prediction model used to calculate the heating/cooling performance of the PVT-HP system has been proposed. And the daily heating guarantee rate and daily cooling guarantee rate have been put forward to evaluate the matching relationship. Based on the evaluation indexes, the applicable matching relationship between the installed capacity of the PVT-HP system and the heating/cooling area of residential buildings has been analyzed. The result of case study shows that for the selected cities of Shenyang, Beijing and Wuhan, the heating/cooling area of residential building for PVT-HP system with installed capacity of 1hp should not exceed 17m2, 31m2 and 25m2, respectively. Further matching analysis of major cities in China shows that the PVT-HP system is more suitable for application in hot summer and cold winter zones of China, in where the suggested heating/cooling area for the PVT-HP system with installed capacity of one horse power is within the range of 30m2 to 37m2.

Exploration of Teaching Reform in Environmental Protection Equipment and Engineering Design Course under the Background of New Engineering

Exploration of Teaching Reform in Environmental Protection Equipment and Engineering Design Course under the Background of New Engineering

Use of Chitosan as a Precursor for Multiple Applications in Medicinal Chemistry: Recent Significant Contributions.

Chitosan (CS) is a polymer made up of mainly deacetylated β-1,4 D-glucosamine units, which is part of a large group of D-glucosamine oligomers known as chitooligosaccharides, which can be obtained from chitin, most abundant natural polymer after cellulose and central component of the shrimp exoskeleton. It is known that it can be used for the development of materials, among which its use stands out in wastewater treatment (removal of metal ions, dyes, and as a membrane in purification processes), food industry (anti-cholesterol and fat, packaging material, preservative, and food additive), agriculture (seed and fertilizer coating, controlled release agrochemicals), pulp and paper industry (surface treatment, adhesive paper), cosmetics (body creams, lotions, etc.), in the engineering of tissues, wound healing, as excipients for drug administration, gels, membranes, nanofibers, beads, microparticles, nanoparticles, scaffolds, sponges, and diverse biological ones, specifically antibacterial and antifungal activities. This article reviews the main contributions published in the last ten years regarding the use and application of CS in medical chemistry. The applications exposed here involve regenerative medicine in the design of bioprocesses and tissue engineering, Pharmaceutical sciences to obtain biomaterials, polymers, biomedicine, and the use of nanomaterials and nanotechnology, toxicology, and Clinical Pharmaceuticals, emphasizing the perspectives and the direction that can take research in this area.

The impact protection behavior of UHPC composite structure on RC columns

In order to prevent the reinforced concrete (RC) structures from being damaged under the overload impact, a new type of composite structure—ultra-high performance concrete (UHPC)–Bio-inspired honeycomb column thin-walled structure (BHTS) was designed in this paper. A scale model with a scaling factor of 1:10 was made. The experimental tests and numerical simulations of RC column and UHPC composite structure were carried out. By comparing the impact force, displacement, shear force, bending moment and energy absorption, the protective effect of the UHPC-BHTS composite structure on RC columns under lateral impact load was evaluated. Then, the failure process of RC column was analyzed, the UHPC-BHTS composite structure absorbed 76.42% of the impact kinetic energy under the higher energy input condition, the shear failure with large damage to the RC column can be converted into bending failure with small damage. At the same time, a new damage assessment method was used to evaluate the RC column. The results show that the RC column with UHPC-BHTS composite structure can effectively protects the RC column structural integrity under impact. The design and modeling methods in this research can provide a useful reference for anti-collision design in practical engineering.

Efficient and durable OER electrocatalysts through vacancy engineering and core-shell structure design in acidic environment

The electrocatalytic conversion of water into green hydrogen energy through overall water splitting advances sustainable energy goals. However, it is limited by the slow kinetics of the oxygen evolution reaction (OER) and durability challenges at high potentials. Here, we rationally develop a series of Mn-doped RuO2-coated Ru (Mn-Ru@RuO2) catalysts involving unique core-shell structures and abundant lattice distortions induced by oxygen defects. The optimal Mn-Ru@RuO2 sample demonstrated robust activity, achieving a low overpotential of 220 mV at 10 mA cm−2. Notably, this sample exhibited minimal degradation after 220 h and a 25.5-fold increase in mass activity (1.37 A mgRu−1) compared to commercial RuO2 at an overpotential of 300 mV. These results suggest that regulated oxygen deficiencies and optimal Ru3+/Ru4+ ratios facilitate the lattice oxygen oxidation (LOM) mechanism and the formation of a high concentration of ∗OH radicals, enhancing acidic OER performance. Additionally, the unique core-shell structures effectively prevent over-oxidation of the RuO2 shell, ensuring superior durability. This research not only breaks the trade-off of electrochemical activity and durability, but also provides valuable insights into the design of highly efficient and stable electrocatalysts.

Design optimization of anti-spin parachute for fighter-class aircraft

Abstract In the absence of spin wind tunnel test and model free flight test support, the traditional empirical formulas had low accuracy and large dispersion, which made it difficult to effectively support the anti-spin parachute design of fighter planes. Based on the principle of spin motion, the empirical formula is modified from two aspects: aircraft aerodynamic layout and mass characteristics. At the same time, the relationship between the parachute area and the flight weight is summarized, which makes the estimated result closer to the actual value and more applicable. In addition, aiming at the problem of excessive load in the design of anti-spin parachutes, the causes of the problem are analyzed in detail. The design criterion of the anti-spin parachute is optimized. Under the premise of ensuring the recovery effect, the need to strengthen the aircraft body structure is effectively reduced. The results show that the engineering estimation methods and design criteria of the anti-spin parachute proposed in this paper are effective after simulation and actual application and can provide technical support for subsequent anti-spin parachute design of new fighter planes.

Review of diver propulsion vehicle: A review

The ocean serves as a vital arena for resource exploitation, scientific inquiry, and strategic endeavors. Among the array of underwater propulsion technologies, diver propulsion vehicles (DPVs) stand out for their exceptional integration, concealability, and maneuverability. They hold a pivotal role in both marine scientific exploration and military operations beneath the waves, thus carrying significant research implications. However, the existing literature on DPVs remains limited, lacking comprehensive examinations of their design processes and parameters. This review systematically surveys and assesses the current landscape of DPV development and research. Three key facets—propeller design, performance assessment, and equipment engineering—are scrutinized and analyzed. By consolidating essential data from ongoing studies, this review offers valuable insights. Additionally, it forecasts potential directions and emerging focal points in the evolution of underwater propulsion for frogmen, drawing from current advancements. The objective is to furnish foundational data to support the design and study of frogman underwater propulsion systems, thereby advancing engineering applications in this domain.

Dynamic Condensation for Efficient Band-Structure Calculations of 2D Periodic Structures

Efficient band-structure calculations are essential for understanding the mechanical behaviors of periodic materials, with significant implications in material design and phononic engineering. This paper introduces the application of the improved reduced system (IRS) technique to expedite elastic band-structure calculations. The IRS, a dynamic condensation method, partitions the unit cell degrees of freedom (DOFs) into primary and secondary sets. A strategic selection of primary DOFs retains a subset of interior DOFs alongside all exterior DOFs while truncating the remaining interior DOFs. The integration of IRS with the Craig–Bampton method for additional reduction and the imposition of Bloch boundary conditions yields a notable decrease in computational overhead. Additionally, for structures with a high number of interior DOFs, a substructuring scheme can be implemented to further enhance efficiency. This approach offers a compelling combination of accuracy and expedited computation, making it applicable across diverse periodic materials.

Structure Analysis of Hybrid Marine Renewable Energy Platform

Abstract The Pilot Project Energy Laut Hybrid for coastal communities utilises a hybrid-based tripod pontoon structure. Hydrodynamic analysis was conducted using Computational Fluid Dynamic (CFD) simulations and Detail Engineering Design (DED) testing at the Hydrodynamics Laboratory of Indonesia (LHI). This research aims to conduct a structural analysis of the tripod pontoon frame, including redesigning and comparing the strength between the existing and modified designs. An analysis using the software SACS V15.1 was employed to obtain unity check values and stress distribution. The analysis revealed that the unity check values for the existing model, with airy wave01, airy wave02, stokes wave01, and stokes wave02, were 0.508, 0.498, 0.509, and 0.5, respectively. In contrast, the unity check values for the modified model, with airy wave01, airy wave02, stokes wave01 and stokes wave02, were 0.827, 0.81, 0.827, and 0.813, respectively, indicating a 63% increase in unity check for the modified model. The largest shear stress was observed on member A5-1-A5-2 in both models, which still complies with the API RP 2A-WSD standard. Additionally, the modified model was 21% lighter than the existing model, with Z shear stress increasing by 63% for both airy and stokes wave types.

Optimization design of composite cap-shape pillar structure based on gaussian process of combined kernel function

Abstract To quickly realize the optimal design of the cap-shaped structure, an optimization design method of composite cap-shaped pillar structure based on combined kernel function Gaussian process was proposed. First, the shortcomings of two kernel functions representing different linear characteristics of data in model construction were analyzed, on which a new combined kernel function was constructed. Based on the finite element numerical simulation results, a database with the web thickness, web height, fiber volume, and ultimate bearing capacity of the cap-shaped structure was constructed. Then, a Gaussian process model based on the combined kernel function was established and the model parameters were trained by the maximum likelihood method. Finally, taking the ultimate bearing capacity per unit volume as the optimization objective, the artificial fish swarm algorithm was used to quickly obtain the structure design parameters under the optimal objective function, and the simulation results were compared with the initial design parameters. The results showed that the method proposed in this paper can optimize the structure performance, improve the design efficiency, and meet the engineering design requirements.

Decoupling method of self-gravity compensation based on spherical multipole expansion for space gravitational wave detectors

In space gravitational wave detection missions, the gravity and its gradients produced by the spacecraft on the two Test Masses (TMs) are commonly referred to as the Self-Gravity(SG). It is an important source of TM disturbances in gravitational wave detection and other drag-free space missions and will affect the TM acceleration noise in many ways. The SG can be reduced by adding Balance Masses (BMs). But for typical space gravitational wave detectors, in which the sensitive axes of the two TMs are at an angle of 60°, the couplings of different SG components of two TMs make the gravity compensation process complicated in practice, which is normally an iterative process. This paper analyses the correspondence between the SG components of the two TMs and the spherical harmonics of different orders, and proposes a compensation method based on spherical multipole expansion. This method allows independent design of the BMs for most of the main SG components, without couplings and iterations. To verify this method, a self-gravity compensation simulation is carried out by using a demonstrating spacecraft structural model for TianQin gravitational wave detection mission. Three sets of BMs are designed on the outer surface of the inertial sensor vacuum chamber, to compensate for the two linear accelerations and one linear gradient that exceed the requirements. The results show that the SG components after compensation are two orders of magnitude lower than the initial level, and all the components meet the preliminary requirements of TianQin mission. This study could provide reference for the engineering design and development of the spacecraft and inertial sensor payload for space gravitational wave detection missions.

Avoiding Flood by Improving Cross-Sectional Capacity through River Normalization

Bekasi is one of the regions in Indonesia that often suffer from flooding. To overcome flooding problems in the Bekasi area, the Ciliwung Cisadane River Basin Center has begun a normalization project along the Bekasi River. This research aimed to evaluate the Bekasi River's cross-sectional capacity both before and after normalization. The analysis focused on the section where the Cileungsi and Cikeas rivers converge to the Bekasi weir. In this research, secondary data were employed, such as national digital elevation model data, detailed engineering designs of Bekasi River flood control activities, and rainfall data from the Cibinong Station that covers the period from 2006 to 2020. The result from planned flood discharge with the Nakayasu synthetic unit hydrograph method for a return period of 25 years on the Bekasi River was obtained at 665.81 m3/s. The results of hydraulic analysis before normalization with the HEC-RAS application show that flooding occurred at 102 out of 116 stations, with capacities of river cross-sections ranging from 453.49 m³/s to 665.71 m³/s at these overflow stations. Following the river normalization process, the cross-sectional capacity at all Bekasi River stations can accommodate flood discharge without any instances of overflow.Keywords: Flood, HEC-RAS, Nakayasu, Normalization, Rainfall.