Initial Design Research Articles

Experiment and Numerical Prediction on Shock Sensitivity of HMX–Based Booster Explosive with Small Scale Gap Test at Low and Elevated Temperatures

In order to analyze the effect of temperature changes on the shock initiation performance of HMX–based booster explosive, which consists of 95% HMX and 5% FPM2602 by weight, a temperature calibration test of acceptor was designed. The temperature changes in the booster at low and elevated temperatures under the constraint of steel sleeve were obtained. Based on the temperature calibration results, polymethyl methacrylate (PMMA) was selected as gap material to conduct a small scale gap test (SSGT) of HMX–based booster under different temperature conditions. The corresponding critical gap thickness was tested. Based on SSGT results at different temperatures, the shock initiation processes were simulated by adjusting parameters of ignition and growth reactive rate model. The critical gap thickness and critical initiation pressure of HMX–based booster at different temperatures were numerically predicted. By combining SSGT experimental data and simulation results, the attenuation law and fitting prediction formula of the critical initiation pressure of HMX–based booster were proposed. The mechanism of temperature effect on the shock sensitivity of HMX–based booster explosive was analyzed. The research results indicate that the critical gap thickness of HMX–based booster gradually increases with the rise in temperature, and the critical initiation pressure gradually decreases during the shock initiation process under the heating temperature conditions. In addition, the simulation results show that the heated HMX–based booster under steel constraints becomes more sensitive at high temperatures (>120 °C), while the cooled booster is more insensitive, but its critical initial pressure does not change significantly between 88 °C and 120 °C. The experimental and numerical prediction results are important for the shock initiation safety and design of an insensitive booster explosive.

Recent Advances and Future Developments in the Preparation of Polypeptides via N-Carboxyanhydride (NCA) Ring-Opening Polymerization.

Polypeptides have the same or similar backbone structures as proteins and peptides, rendering them as suitable and important biomaterials. Amino acid N-carboxyanhydrides (NCA) ring-opening polymerization has been the most efficient strategy for polypeptide preparation, with continuous advance in the design of initiators, catalysts and reaction conditions. This Perspective first summarizes the recent progress of NCA synthesis and purification. Subsequently, we focus on various initiators for NCA polymerization, catalysts for accelerating polymerization or enhancing the controllability of polymerization, and recent advances in the reaction approach of NCA polymerization. Finally, we discuss future research directions and open challenges.

Evaluation on Network Social Media Named Entity Recognition Model Based on Active Learning

The medical security privacy and named entity recognition (NER) technology under the blockchain technology has been a hot topic in all walks of life. As a typical representative of medical security risks and NER, the NER model of online social media based on active learning has attracted worldwide attention. NER is an important part of natural language processing. Traditional recognition technology usually requires a lot of external information, and through the manual identification of its features, which costs a lot of time and energy. In order to solve the shortcomings of traditional recognition algorithms and the lack of feature extraction in network media NER, a new active learning model was introduced in this paper. In the information age, people are increasingly demanding a large amount of text information, and NER technology came into being. Its main function is to accurately identify important information from text and provide useful information for high-level work. The initial design of NER system is mainly based on the recognition of rules, so as to realize the recognition of named entities. However, in a complex network environment, it takes a lot of time and energy to establish rules without conflicts, and it has poor mobility. In recent years, with the continuous development of computer technology, the use of machine learning to actively learn the unknown information in the target area reduces the workload of manual annotation, thus realizing the active learning of large amounts of data. The research showed that the recognition accuracy under the traditional NER was low, and the information processing speed was slow; the accuracy rate of NER based on active learning was as high as 97%, and the speed of information processing had also been greatly improved, which had solved many problems under the traditional mode. User satisfaction could be as high as 95%, which showed that the latter had broad prospects. The progress of the new era cannot be separated from the support of new technologies. The research of this article has important guiding significance for medical security privacy and the application of NER under blockchain technology.

Design and Analysis of Surface-Mounted Permanent-Magnet Field-Modulation Machine for Achieving High Power Factor

Along with the establishment of general air-gap field modulation theory, a new type of field-modulation machine has attracted increasing attention. However, the low power factor always plagued its popularization. This paper is to focus on the simplest structure surface-mounted permanent-magnet field-modulation (SMPMFM) machine, aiming at exploring the implementation of high power-factor design. The key is that the power factor calculation formula is derived parametrically, hence the originally vague causal relationship between the structural parameters and power factor become clear, guided by which the initial structure design for high power factor achievement is determined, meanwhile the power factor adjustment evaluation and the electromagnetic performance comparison with the help of finite element analysis (FEA) are conducted to verify the validity of the proposed power factor calculation formula. Finally, a feasible high-power-factor SMPMFM prototype is fabricated and the experimental testing is performed, which has a good agreement with the formular calculation and FEA results. Hence, the validity of the proposed analysis for achieving high power-factor design of field-modulation machines is verified.

Infrastructure digital twin technology: A new paradigm for future construction industry

The construction industry has traditionally been slow to adopt digital technology, resulting in inefficient workflows, frequent cost overruns, and delays. Moreover, its fragmented structure, inherent to market dynamics, exacerbates these challenges. Embracing digitalization and transitioning to Industry 4.0 can substantially enhance efficiency and productivity in construction through increased innovation and improved collaboration, ultimately reducing information gaps and data discrepancies. This study aims to assess the potential integration of digital twin technology across various construction stages, spanning from initial design to project delivery. Existing literature emphasizes the transformative power of digital twin technology in advancing building innovation and environmental sustainability. These virtual replicas are crucial in optimizing industrial manufacturing by harmonizing production processes and societal interactions. A focused examination of digital twin technology applications in construction highlights its ability to streamline coordination and facilitate data sharing among stakeholders. Property owners increasingly recognise the value of digital twin technology in local contexts, driving the digitization of design and collaboration methods in construction. Integrating digital twin technology right from a project's inception and extending it across design phases optimizes project delivery, enhances asset quality, and contributes to societal sustainability. As the nexus between digitalization and sustainability goals strengthens, the construction industry stands at the cusp of a significant transformative journey.

Bayesian Optimization via Exact Penalty

Constrained optimization problems pose challenges when the objective function and constraints are nonconvex and their evaluation requires expensive black-box simulations. Recently, hybrid optimization methods that integrate statistical surrogate modeling with numerical optimization algorithms have shown great promise, as they inherit the properties of global convergence from statistical surrogate modeling and fast local convergence from numerical optimization algorithms. However, the computational efficiency is not satisfied by practical needs under limited budgets and in the presence of equality constraints. In this article, we propose a novel hybrid optimization method, called exact penalty Bayesian optimization (EPBO), which employs Bayesian optimization within the exact penalty framework. We model the composite penalty function by a weighted sum of Gaussian processes, where the qualitative components of the constraint violations are smoothed by their predictive means. The proposed method features (i) closed-form acquisition functions, (ii) robustness to initial designs, (iii) the capability to start from infeasible points, and (iv) effective handling of equality constraints. We demonstrate the superiority of EPBO to state-of-the-art competitors using a suite of benchmark synthetic test problems and two real-world engineering design problems.

Development and Implementation of an FPGA-Embedded Multimedia Remote Monitoring System for Information Technology Server Room Management

Conventional data acquisition systems face challenges in achieving high acquisition speeds and rapid storage of large data volumes using microcontrollers. In contrast, field-programmable gate arrays (FPGAs) offer numerous advantages, including high clock frequencies, minimal internal delays, fast operational speeds, abundant internal RAM resources, and simplified control of complex peripheral circuits. This study presents the design of an FPGA-based multimedia remote monitoring system for information technology server rooms. The proposed system utilizes an FPGA as the primary controller and incorporates environmental sensors, electrical energy sensors, carbon monoxide sensors, smoke sensors, and A/D converter modules to monitor multiple locations within the server room. Simultaneously, the FPGA transmits the collected data from each monitoring point via a serial port to an LCD serial screen for display. An alarm is triggered if any environmental anomalies are detected, indicating abnormal statuses. Additionally, the system employs the fast Fourier transform algorithm and butterfly operations to derive voltage and current AC quantities, while utilizing relative temperature differences to identify equipment faults within the server room. The system is evaluated in terms of functionality, user-friendliness, and reliability. Experimental results demonstrate that all performance measures align with expectations, fulfilling the initial design objectives and highlighting the potential applicability and relevance of FPGA technology in the monitoring field. In addition, a comparison between FPGA and traditional microcontroller systems is performed, showcasing the superior processing speed and performance of the FPGA-based system. This comparative analysis further validates the advantages of using FPGA technology in high-speed data acquisition and monitoring applications.

Aerodynamic Investigation of Propulsion Integration for a Low Noise Hybrid Wing-Body with Podded UHBR Turbofan Engines

The presented work examines the aerodynamic challenges of podded ultra high-bypass engines installed on a short/mid range low noise hybrid wing body configuration. After assessing the initial engine integration design, sensitivity studies regarding the impact of the freestream Mach number, engine position, and the engine incidence angle on the interference drag are discussed. Then, shape modifications of the nacelle and the center-body based on 2D RANS optimizations are presented. The results indicate that in order to reduce the initially massive interference drag, the overall aircraft design either has to allow for a modified engine position or for reshaping of the center-body’s upper surface. With the latter, an overall drag reduction of –44 % was achieved.

Mapping using an adaptive sampling design

Interpolation is commonly used in the construction of maps and images when there is limited information for some of the sites. The accuracy of interpolation methods depends, in part, on the location of the sample sites where more complete information has been gathered. An initial survey design where the sample sites are spaced so there is wide-spread coverage is desirable. However, when there is considerable variation in the variable of interest, other design features may be preferable. Here we introduce an adaptive design where in the first stage of site selection gives wide-spread coverage, and in subsequent stages additional sites are selected adjacent to areas of high variability.

Kinematic Performance of a Customizable Single Degree-of-Freedom Gait Trainer for Cost-Effective Therapy Aimed at Neuromuscular Impairments

Abstract A majority of robotic gait trainers to facilitate physical therapy for gait rehabilitation in humans are based on multidegree-of-freedom exoskeleton-based systems with sophisticated electro-mechanical hardware and software, and consequently remain inaccessible to vast sections of the populations around the world. This study seeks to advance the development of a single degree-of-freedom (DOF) gait trainer for gait therapy for individuals with neuromuscular impairments. The goal is to offer a cost-effective, accessible solution to cater to the global need for gait rehabilitation. We build upon the previous gait trainer design based on Jansen mechanism and provide an in-depth analysis and experimental validation of its kinematic performance. The device's performance is also tested and successfully demonstrated through trials involving two healthy individuals to examine its kinematic behavior under human-induced load conditions. The gait trainer demonstrates satisfactory performance under both no load conditions and a 2 kg load, exhibiting an area difference of 1% and 7%, respectively. However, when subjected to a 5 kg loading condition, a significant area difference of 27% is observed, primarily attributed to the cantilever loading at the driving shaft. A method to adjust link lengths based on specific human gait trajectories is proposed and validated. Additionally, a cost-effective tool for ankle trajectory measurement is introduced to establish a ground truth. The study demonstrates the potential of an affordable, single DOF gait trainer in facilitating high-volume therapy for those with walking disorders. This research represents a step toward making gait therapy more accessible worldwide.

Development of the nursing associate professional identity: A longitudinal qualitative study.

The aim of this study was to understand the factors that contribute to the development of the nursing associate professional identity. A 3-year longitudinal qualitative study of trainee nursing associates. Trainee nursing associates in England were interviewed remotely annually in February 2020, March 2021 and March 2022. They also provided diary entries. Data were anonymised, transcribed and analysed thematically. Nursing associate professional identity was developed through: increased knowledge, skills and responsibility; and self-perceptions of identity alongside responses to the role by colleagues. Tensions arose when the scope of practice expected by organisations differed from that expected by the nursing associates. Frustrations occurred when nursing associates were perceived as substitutes for Registered Nurses in the context of nursing workforce shortages. Nursing associates in this study clearly valued their new knowledge, skills and responsibility, enabling them to provide enhanced patient care. Increased clarity of role boundaries is necessary in enhancing the professional identity of nursing associates and reducing inter-professional tensions arising from role ambiguity within health and social care organisations. National guidance and employers should provide clarity on the boundaries of the nursing associate role which will strengthen their professional identity and mitigate role ambiguity within health and social care organisations. The Consolidated Criteria for Reporting Qualitative Research has been used to guide reporting. A patient and public involvement group was consulted during the initial study design stage. This study aimed to understand the factors which contribute to the development of a nursing associate professional identity. Nursing associate professional identity is developed through increased knowledge, skills and responsibility, and the perceptions of identity by participants themselves and their colleagues. The findings should inform the implementation of initiatives to clarify nursing associate role boundaries and the development of similar roles internationally.

Effects of a conductive T-shaped partition on the phase change dynamics in a channel equipped with multiple encapsulated PCMs under different magnetic fields

For enhanced thermal management and energy storage, an understanding of the phase change process and how to control it is crucial in many different engineering applications. In this study, effects of using a T-shaped conductive partition on the phase change process in a multiple phase change material-installed three dimensional cylinder are explored by using finite element method. In the computational domain, a uniform magnetic field with varying strengths is applied. The investigation is conducted for various Reynolds numbers (Re:200–500), Hartmann number of the first and second domains (Ha1: 0–50 and Ha2: 0–50), partitions sizes (Lp: 0.05L–0.5L), and conductivity ratios (KR:0.01–100). The entire transition times (trF) of the left and right phase change materials decrease with increasing Re and Ha. At Ha1=0, the reduction amounts of trF with Re for phase change materials P1 and P2 are 24.40% and 27.45%, respectively. When magnetic field is imposed at Ha1=50, the amounts are 19.4% and 22.7%. The size of the conductive partition affects the size of the vortex established within the phase change material zone. When the partition size is altered, the tr-F variation for P1 and P2 in the absence of magnetic field is 11% and 8.5%, respectively, but in the presence of magnetic field it is 26.5% and 7%. The partition’s conductivity has an impact on the dynamics of phase changes as well. The phase completion times of the various phase change materials differ most at KR=0.1, and at that moment, P1’s trF is 42% higher than P2’s. When modeling the time-dependent variation of liquid fraction for various phase change materials and conductivity ratios, a polynomial type regression model is employed. The findings are useful for the initial design, thermal management and the optimization studies of phase change material embedded systems in a variety of applications, such as heat recovery systems, convective heat transfer applications, and the cooling of electronic equipments.

A Study on Deformation due to Steel Constraint during Butt Welding and Line Heating of Thick-Plate in FLNG Topside Bearing Node

Products manufactured in shipyards are predominantly steel structures, primarily fabricated through welding. There are various welding methods, all of which commonly use very high heat. Therefore, during the fabrication of steel structures, thermal deformation caused by welding occurs, resulting in dimensional deviations from the initial design. Methods to ensure dimensional accuracy include optimizing the welding sequence, predicting thermal deformation before welding and applying reverse-setting, and suppressing thermal deformation through constraints. However, the most commonly used method in the field is heat straightening. This study proposes a method to control thermal deformation caused by welding by using steel constraints during welding and line heating. Analytical verification confirmed both the effect of heat straightening and the variance in effects when steel constraints were applied. As a result, it was confirmed that line heating is effective in correcting thermal deformation, and steel constraints can maximize the effect of line heating.

Efficiency of utilizing building information modeling tools for examining smart materials behavior in a hot climate

The significance of smart materials aligns seamlessly with promoting the seventh goal of Sustainable Development, given their adaptability and energy-efficient properties in the construction sector. Using BIM tools to simulate environmental performance can enhance understanding of the behavior of smart materials within building components. Therefore, this study proposes integrating genetic algorithms (GA) with Building Information Modeling (BIM) through the Dynamo plugin. Where genetic algorithms help link the properties of smart materials and external stimuli, which outperforms traditional simulation tools for energy analysis.A comparison between the analysis process in Dynamo and Green Building Studio (GBS) emphasizes Dynamo's efficiency in simulating energy performance within the BIM environment in a shorter process. The effectiveness of simulating smart materials in Dynamo was validated in a hot climate through two scenarios of Phase change materials (BioPCM 29) and thermochromic materials (TCM), that were used in a lecture hall in an educational building in the Faculty of Engineering at Port Said University. Through the heat transfer rate indicator, energy consumption reduction rates were calculated. Integrating (BioPCM 29) into walls, ceilings, and glazing demonstrated a notable reduction in energy consumption for cooling in the summer months by a rate ranging between 23.3% and 23.4%. While (TCM) helped reduce consumption by 19.3%–19.4% in the same period of months. These findings affirm the research objective, highlighting BIM's potential as a tool to compare the environmental performance of smart materials and thus reach the optimal choice from the initial design stages.

Designing, refining and reflecting on 3 years of daily evidence surveillance for Australia's living national COVID‐19 guidelines

AbstractAustralia's national living guidelines for COVID‐19 were launched in April 2020 and include over 200 recommendations to guide the clinical care of patients with COVID‐19. Until the guidelines were retired in August 2023, new evidence was continually monitored through daily surveillance. This paper describes the initial design for evidence surveillance (at a time when efforts to collate information on the novel coronavirus were in their infancy and often duplicative) and how it was refined throughout the pandemic. Among the wide range of sources monitored, the collections of COVID‐19 research from leading medical journals, medRxiv preprints and PubMed auto alerts proved the most enduring in identifying time‐critical and impactful evidence. The paper also explores how evidence was tracked and surveillance integrated into the overall evidence workflow by using messaging apps and communication platforms. Finally, we consider the implications for living guidelines and reflect on factors that contributed to the feasibility of daily surveillance: the clearly defined scope of the guidelines; focusing efforts on maximum impact; minimizing duplication by partnering with others; setting up simple but effective processes for managing evidence; and the value of continuous involvement of personnel from the outset. Australia's living COVID‐19 guidelines were underpinned by a novel approach to evidence surveillance that was feasible and essential in maintaining COVID‐19 living guidelines for over 3 years.

Rate-dependent damage sequence interaction model for predicting the mechanical property of in-service aluminum alloy 6005A-T6

Engineering structures and materials will undergo fatigue, aging, and other degradation behaviors during long-term service under the combined influence of complex boundary conditions. These service damages make the materials and structures no longer meet the initial design requirements and pose a potential risk to the service system. This study proposes a material mesoscopic model to decouple the microstructure into a system composed of matrix and void phases. The matrix phase has an invariant constitutive relationship as an ideally undamaged material, and the different evolutionary behaviors of the void phase are described as damage evolution functions and lead to different stress–strain behaviors of the actual material. First, the damage described by different definitions is proposed, and a nonlinear function of damage evolution consistent with the Weibull distribution characteristic of microstructural continuity is derived. Then, an experimental–numerical method is improved to accurately identify the accelerated damage evolution behavior under various strain rates. Finally, the ideally undamaged constitutive of the matrix phase and the damage evolution function of the void phase are established, which can cover the void nucleation, growth, and aggregation process. Besides, the damage sequence interaction model is established in conjunction with the mesoscopic physical mechanism, and the total damage evolution function for materials containing prior service damage in subsequent ductile deformation is achieved by measuring the apparent elastic modulus of the material only. Finally, the ideally undamaged constitutive and damage evolution function are calibrated for aluminum alloy 6005A-T6, commonly used in the car body structure of rail vehicles, and verified with damaged specimens that experienced certain service loads. The material's damage sequence interaction mode is determined, and the rate-dependent residual strength is predicted.

Combined Soft Grasping and Crawling Locomotor Robot for Exterior Navigation of Tubular Structures

This paper presents the design, development, and testing of a robot that combines soft-body grasping and crawling locomotion to navigate tubular objects. Inspired by the natural snakes’ climbing locomotion of tubular objects, the soft robot includes proximal and distal modules with radial expansion/contraction for grasping around the objects and a longitudinal contractile–expandable driving module in-between for providing a bi-directional crawling movement along the length of the object. The robot’s grasping modules are made of fabrics, and the crawling module is made of an extensible pneumatic soft actuator (ePSA). Conceptual designs and CAD models of the robot parts, textile-based inflatable structures, and pneumatic driving mechanisms were developed. The mechanical parts were fabricated using advanced and conventional manufacturing techniques. An Arduino-based electro-pneumatic control board was developed for generating cyclic patterns of grasping and locomotion. Different reinforcing patterns and materials characterize the locomotor actuators’ dynamical responses to the varying input pressures. The robot was tested in a laboratory setting to navigate a cable, and the collected data were used to modify the designs and control software and hardware. The capability of the soft robot for navigating cables in vertical, horizontal, and curved path scenarios was successfully demonstrated. Compared to the initial design, the forward speed is improved three-fold.

Design optimization of the bamboo-inspired foam-filled tube for high-speed train collision energy absorption

This study first developed a novel bamboo-inspired foam-filled tube (BFFT) for potential application in high-speed trains, considering the practical use conditions. The BFFT was initially designed by mimicking the macro and micro characteristics of bamboo culms and understanding their axial crushing mechanical behavior. The key bionic parameters are drawn based on the crashworthiness indices of natural bamboos with various geometric sizes and growth ages. The numerical simulation model of the BFFT under axial impact load was established and verified using simplified super folding element (SSFE) theory and drop-weight experiments. A multi-objective optimization on the BFFT was conducted to find the optimal parameter alternative, integrating experimental design method of the optimal Latin hypercube, the response surface agent model and the non-dominated sorting genetic algorithm (NSGA-II). The crashworthiness performance of the optimized BFFT was compared with the initial design scheme, a conventional circular tube and other existing energy absorbers of rail vehicles. The results indicated that the EA, SEA and IPCF values of the optimized BFFT can be improved by 150.2 %, 63.3 %, and 48.5 %, respectively, when considering the single target requirement. In comparison to the initial design scheme and conventional circular tube, the SEA value of the final optimized BFFT increased by 44.7 % and 53.0 %, respectively. The proposed novel BFFT demonstrated a superior crashworthiness, providing inspiration for enhancing and optimizing passive safety performance of high-speed trains.

Designing small batteries and adaptive charging strategies for operation on rough terrain

The global trajectory is swiftly progressing towards the adoption of electric vehicles (EVs). Given that batteries constitute a pivotal component within the domain of EV technology, their performance and life have become of utmost importance. Battery life is affected by multiple internal and external factors. This paper addresses real-time challenges associated with using battery packs in dynamic on-road conditions characterized by variable discharge rates, temperatures, depth of discharge, storage conditions, and rough terrains. The study involves designing 2.8kWh battery packs and using them to power e-rickshaws in on-road conditions in places like India. The study shows how minor issues, which are often overlooked during the initial pack design phase, can impact the long-term operational performance of the batteries.In real-world scenarios, users lack control over the discharge of a battery. However, the charging process can be effectively controlled. In this paper, we propose an adaptive slow-charging strategy to prolong the life of the battery pack. The suggested charging algorithm regulates the charging current based on parameters such as battery temperature, state of health, and terminal voltage. To assess the impact of this algorithm, we conducted tests on 2.8kWh battery packs used in e-rickshaws for over two years under real-world driving conditions. The effectiveness of the proposed algorithm is demonstrated by comparing the battery degradation with the standard constant current constant voltage charging. The study also introduces a novel balancing technique involving temporary suspension of balancing and charging currents during voltage measurements, mitigating errors linked to ohmic drops. Additionally, the research examines the degradation caused by parking vehicles for extended periods.

Modern software capabilities for shape optimization of shells

The article is devoted to the shape optimization of shell structures in Comsol Multiphysics using three gradient-based methods: IPOPT (Interior Point OPTimizer), SNOPT (Sparse Nonlinear OPTimizer) and MMA or GCMMA (the Method of Moving Asymptotes). Two types of complex shapes, such as right helicoid and developable helicoid are taken for the computational experiment. The task is to investigate the initial design and optimization process of two helicoids. To obtain a more accurate result and an interesting design solution, the calculation is carried out using three physics-controlled mesh sizes: extra coarse, fine and extra fine with varying values of special optimization settings, such as maximum displacement (dmax) and filter radius (Rmin). The results obtained using the three methods allow to conclude that the mesh element size and studied parameters dmax and Rmin have a significant impact on the final optimization result.