Design Stage Research Articles

A systematic assessment of robustness in CNS safety pharmacology.

Irwin tests are key preclinical study elements for characterising drug-induced neurological side effects. This multicentre study aimed to assess the robustness of Irwin tests across multinational sites during three stages of protocol harmonisation. The projects were part of the Enhanced Quality in Preclinical Data framework, aiming to increase success rates in transition from preclinical testing to clinical application. Female and male NMRI mice were assigned to one of three groups (vehicle, MK-801 0.1and 0.3 mg kg-1). Irwin scores were assessed at baseline and multiple times following intraperitoneal injection of MK-801 using local protocols (Stage 1), shared protocols with harmonised environmental design (Stage 2) and fully harmonised Irwin scoring protocols (Stage 3). The analysis based on the four functional domains (motor, autonomic, sedation and excitation) revealed substantial data variability in Stages 1 and 2. Although there was still marked overall heterogeneity between sites in Stage 3 after complete harmonisation of the Irwin scoring scheme, heterogeneity was only moderate within functional domains. When comparing treatment groups versus vehicle, we found large effect sizes in the motor domain and subtle to moderate effects in the excitation-related and autonomic domains. The pronounced interlaboratory variability in Irwin datasets for the CNS-active compound MK-801 needs to be carefully considered when making decisions during drug development. While environmental and general study design had a minor impact, the study suggests that harmonisation of parameters and their scoring can limit variability and increase robustness.

A flexible and fast digital twin for RRAM systems applied for training resilient neural networks

Resistive Random Access Memory (RRAM) has gained considerable momentum due to its non-volatility and energy efficiency. Material and device scientists have been proposing novel material stacks that can mimic the “ideal memristor” which can deliver performance, energy efficiency, reliability and accuracy. However, designing RRAM-based systems is challenging. Engineering a new material stack, designing a device, and experimenting takes significant time for material and device researchers. Furthermore, the acceptability of the device is ultimately decided at the system level. We see a gap here where there is a need for facilitating material and device researchers with a “push button” modeling framework that allows to evaluate the efficacy of the device at system level during early device design stages. Speed, accuracy, and adaptability are the fundamental requirements of this modelling framework. In this paper, we propose a digital twin (DT)-like modeling framework that automatically creates RRAM device models from device measurement data. Furthermore, the model incorporates the peripheral circuit to ensure accurate energy and performance evaluations. We demonstrate the DT generation and DT usage for multiple RRAM technologies and applications and illustrate the achieved performance of our GPU implementation. We conclude with the application of our modeling approach to measurement data from two distinct fabricated devices, validating its effectiveness in a neural network processing an Electrocardiogram (ECG) dataset and incorporating Fault Aware Training (FAT).

QUALIMETRIC MODEL OF A HIGH-TECH INFORMATION AND MEASURING SYSTEM FOR THE PREPARATION AND CONDUCT OF TESTS

The issue of the report concerns the selection of information and testing equipment or a system that will be used for planning and conducting tests with minimal error and high efficiency. The complexity of consideration as a whole, when choosing the components of the information and measurement system and determining the qualitative measurement model determines the need to divide it into several stages and consider them separately. The stages of building a qualitative model of a high-tech information and measurement system for preparing and conducting tests are divided into: modeling stage; design stage; stage of implementation; interpretation stage. At the stage of determining the limitations, it should be taken into account in which division the tests are carried out, namely: by purpose; by the level of testing; by stages of product development; by testing finished products; according to the conditions and venue; by the duration of the tests; by type of action; by the result of the action; according to the characteristics of the object. The relevance of the work is the consideration of the stages of building a qualitative model of the information and measurement system in the difficult conditions of the military and political situation in Ukraine. The purpose of the work is to develop the technological aspects of qualitative modeling, as well as the stages of qualitative model examination. Additional results of the work can be – to obtain initial data (parameters); – to break down important indicators (parameters) according to their importance using an expert method; – to assess state and foreign requirements for the system for further work; – to assess and choose a direction based on the price indicator (factor) and duration of work or other indicators; – provide recommendations for making a decision regarding the construction of a qualitative model of the properties of the information and measurement system;–allow to improve (apply) the process of conducting tests of high-tech weapons and military equipment; – allow to use qualitative model databases to reduce preparation time to conducting tests of high-tech weapons and military equipment;–will allow to expand the directions for finding new features and providing recommendations in the further process of tests. The article builds a qualitative model (hereafter KM) of the formation (creation) of KM stages of the information and measurement system (hereafter IMS) at the preparatory stage of OVT tests. Stages of KM examination have been developed based on the current purpose of the tests, the required quantity and quality of recorded and measured indicators, the complexity of measurements and their analysis. Formulated KM efficiency indicators are as follows: minimal error; cost of equipment; equipment resource; others. The stages of selection of IBS components have been developed and the KM of assessment at the preparatory stage of tests has been determined. A model of quantitative quality measurement has been developed, taking into account possible errors and the provided, structural, technological aspects and stages of qualitative modeling. The most expedient tool for a systematic approach to decision-making during the construction of the IBS CM has been determined. The results of a similar review of literary sources of domestic and foreign scientists are presented. However, the insufficient development of the scientific basis for creating KM efficiency indicators is noted. The normative and real vectors of the creation of the CM are determined, which are laid down as important indicators of the effectiveness of the CM, by changing which it is possible to change the direction of the selection of the creation of the CM of the IAS.

Visual Anomaly Detection via CNN-BiLSTM Network with Knit Feature Sequence for Floating-Yarn Stacking during the High-Speed Sweater Knitting Process

In order to meet the current expanding market demand for knitwear, high-speed automatic knitting machines with “one-line knit to shape” capability are widely used. However, the frequent emergence of floating-yarn stacking anomalies during the high-speed knitting process will seriously hinder the normal reciprocating motion of the needles and cause a catastrophic fracture of the whole machine needle plate, greatly affecting the efficiency of the knitting machines. To overcome the limitations of the existing physical-probe detection method, in this work, we propose a visual floating-yarn anomaly recognition framework based on a CNN-BiLSTM network with the knit feature sequence (CNN-BiLSTM-KFS), which is a unique sequence of knitting yarn positions depending on the knitting status. The sequence of knitting characteristics contains the head speed, the number of rows, and the head movements of the automatic knitting machine, enabling the model to achieve more accurate and efficient floating-yarn identification in complex knitting structures by utilizing contextual information from knitting programs. Compared to the traditional probe inspection method, the framework is highly versatile as it does not need to be adjusted to the specifics of the automatic knitting machine during the production process. The recognition model is trained at the design and sampling stages, and the resulting model can be applied to different automatic knitting machines to recognize floating yarns occurring in various knitting structures. The experimental results show that the improved network spends 75% less time than the probe-based detection, has a higher overall average detection accuracy of 93% compared to the original network, and responds faster to floating yarn anomalies. The as-proposed CNN-BiLSTM-KFS floating-yarn visual detection method not only enhances the reliability of floating-yarn anomaly detection, but also reduces the time and cost required for production adjustments. The results of this study will bring significant improvements in the field of automatic floating-yarn detection and have the potential to promote the application of smart technologies in the knitting industry.

Development of a Program for Searching the Optimum Condition using the Design of Experiments

The Design of Experiments (DOE) is a method that is widely used due to its effectiveness in selecting optimum conditions in the design stage of product development. On the other hand, fast, low-cost, labor-saving, and energy-saving innovative development is also required in the industry. In previous research, a program for quickly searching the optimum condition using the design of experiments is developed and evaluated. Relationships between each parameter and the final property are firstly cleared for an algebraic formula by using the design of experiments. Then the optimum conditions for each parameter were decided by using these formulas in the program. However, when each parameter has several errors in the data, the search accuracy becomes very low. In this research, the improvement for the searching accuracy using the law of error propagation was developed and evaluated. Relationships between each parameter error and the final property are firstly cleared for high-accuracy searching by using the law of error propagation and the previous results in the previous research. And each parameter influence for the final property was cleared. It was found that the large parameter effects could be improved for high-precision search by using high-precision instruments, increasing the number of trials N, and taking measurements in an optimal environment. Relationships between each parameter error and the final property were investigated and evaluated for the proposed method by using a mathematical model. It is concluded from the result that (1) the proposed method is effective for clearing the relationships between each parameter error and the final property, and (2) the proposed method is effective for searching the optimum condition.

Life cycle assessment and generative design: development of a national LCA tool for exterior walls

PurposeThe promotion of sustainable design is demanded globally. The life cycle assessment (LCA) proved its reliability in this mission, but the difficulty and time required to apply it discouraged designers. This research aims to integrate LCA into the building design process through a software tool, taking advantage of generative design features. This will facilitate decision-making by architects and construction professionals.Design/methodology/approachThe study develops the EGY-LCA (http://egy-lca.com/). This prototype tool suggests exterior wall design alternatives for residential buildings in Egypt, using the environmental impact indicators of LCA data and other criteria related to national codes, materials, construction methods and required thermal resistance. Within a generative design process, the algorithm tests every possible wall method with materials and thickness combinations for each layer in compliance with inputs. The paper begins by explaining the tool’s working method. Afterward, different sets of inputs are examined and the values of the resultant environmental impacts of several suggested wall solutions are statistically analyzed. The application demonstrates the importance of the generative design tool. Proposing several solutions based on a set of inputs facilitates the selection of sustainable choices and allows comparisons between alternatives.FindingsThe prototype experiment confirms the research hypothesis. Unlike the available LCA tools, architects can make decisions with limited LCA experience if the data and equations are integrated into a generative design tool. The prototype proves its applicability for exterior wall alternatives.Research limitations/implicationsThe prototype is the initial step toward a whole-building LCA tool. It includes limited LCA stages and materials for the external wall. Future research is required to expand this parametric tool concept to include all the building components. The framework in Section 5 proposes a visualization.Practical implicationsThe prototype tool: EGY-LCA (http://egy-lca.com/). The value added to the design and construction sectors through the uncomplicated LCA application is fostering sustainable design, generative design tools can achieve this.Originality/valueThe novelty of this work is that it is the first initiative offering a parametric LCA tool. It promotes the application of LCA at the design stage using generative design, which contributes to sustainable development.

Observation and Prediction of Instability due to RD Fluid Force in Rotating Machinery by Operational Modal Analysis

In recent years, as rotating machinery has become smaller and more efficient, various types of shaft vibration problems have arisen. Failure of rotating machinery may lead to major accidents and infrastructure shutdowns. Therefore, to prevent failures of rotating machinery, there is a growing need for the vibration analysis technology at the design stage and condition monitoring during operation stage. One of causes of the shaft vibration problems in rotating machinery is the rotordynamic (RD) fluid force acting on fluid elements such as journal bearings, seals, turbine blades, and so on. RD fluid force has a significant effect on the stability of rotating machinery and can destabilize the system. In recent years, operational modal analysis (OMA) methods, which identify modal parameters based on the measured data of a machine's operational condition, have been investigated in the condition monitoring. In this paper, the estimation of the modal parameters of rotating machinery using OMA from only the time history response of displacement data and, in particular, the prediction of the destabilization of rotating machinery caused by RD fluid force are investigated. As a result, the modal parameters are well estimated and, in particular, the destabilization of one mode due to RD fluid force is predicted and explained. The results are in good agreement with the results of the eigenvalue analysis of the original system, and the method is validated. Furthermore, the proposed method is applied to experimental data of the system destabilized by fluid force. The change in stability with rotational speed is observed, and the characteristics of the mode toward destabilization are confirmed. The results show the validity of OMA's predictions of destabilization in the experiments.

Performance analysis of meta-heuristic optimization techniques for multi-objective VLSI circuit partitioning

Abstract The efficiency of various stages of physical design in the Very Large Scale Integration (VLSI) circuit can be enhanced by using multi-objective optimization techniques. The circuit is partitioned into a set of modules at the beginning of the physical design phase. This step is known as circuit partitioning. All subsequent physical design stages, like floor planning, placement, pin configuration, and routing etc, are influenced by the outcome of the circuit partitioning method being used. The efficiency of the partitioning method controls the quality of ultimate architecture. The efficiency achieved by the final product may be decreased by incorrect partitioning. This study compares the effectiveness of four Meta-heuristic optimization methods include the Genetic Algorithm (GA), Satin Bowered Bird (SBO), Particle Swarm Optimization (PSO), Simulated Annealing (SA) — in terms of number of net cut, duration of sleeping mode, and efficiency in power consumption for addressing the VLSI circuit partitioning problem. This experiment achieves K-way partitioning of the circuit that minimizes net cuts as well as maximizes sleep duration simultaneously, by evaluating optimization function. Solutions developed using GA, SBO and PSO consistently surpass those acquired using SA with respect to quality of optimal solution. The average optimum net cut and sleep duration achieved by this experiment are 10.7 and 9.9 in GA ; 11.5 and 12.3 in SBO, 11.80 and 9.10 in PSO; and 16.8 and 6.7 in SA based method respectively. This research resulted in a considerable reduction in power consumption, with the system’s average power efficiency achieved by 21.6%, 26.84%, 19.85%, and 14.62%, respectively, in GA, SBO , PSO, and SA based optimizations. The experimental results are compared with a recent publication and proposed GA, SBO, and PSO based methods achieve 18.75%, 4.17%, and 1.04% improvement in terms of average net cut respectively. The proposed GA, SBO, PSO and SA based methods also achieve 44.90%, 51.30%, 40.05%, and 18.60% improvement in terms of average power efficiency.

Anomalous release of indoles from amorphous solid dispersion formed with a polymeric network

AbstractAmorphous solid dispersion (ASDs) is a technique used in the pharmaceutical industry to enhance the solubility, dissolution rate, and bioavailability of poorly soluble drugs. Polymeric materials, and recently polymer gels form and stabilize the amorphous structure by inhibiting the aggregation/precipitation of such drugs. In this work indole, 5-aminoindole and 5-hydroxyindole loaded poly (N-isopropylacrylamide) (PNIPA) hydrogels were studied. Swelling and uptake measurements, X-ray diffraction (XRD), liquid and solid phase nuclear magnetic spectroscopy (NMR) and high sensitivity differential scanning calorimetry (DSC) were applied to understand the drug – matrix interactions affecting the release. We confirmed that the hydrogel fostered the fine uniform distribution of the hydrophobic probe molecules and successfully prevented any crystalline or amorphous phase formation during water removal, leading to a glassy solution, a special form of ASD. Despite the limited difference between their chemical composition the probe molecules showed dissimilar drug release behavior from dried loaded gel disks. While Nuclear Overhauser Enhancement Spectroscopy (NOESY) measurements revealed a “bidental” interaction between 5-hydroxiindole and the polymer, no localized interactions were found for indole. The release of the bidentally linked derivatives is rapid and complete: they act as molecular spacers, promoting the rehydration of the chains. In contrast, part of the indole remains irreversibly trapped being confined between the chains without any orientation, shedding light on the role of the steric consequences of the interaction. Our findings also indicate that such drug delivery compositions should be treated as ternary systems (carrier + drug + liquid) already in the design stages of drug release systems.

АНАЛІЗ ВПЛИВУ КУТА СТРІЛОПОДІБНОСТІ НА ХАРАКТЕРИСТИКИ СТАТИЧНОЇ АЕРОПРУЖНОСТІ КРИЛА НАВЧАЛЬНО-ТРЕНУВАЛЬНОГО ЛІТАКА

The article is dedicated to the analysis of static aeroelastic phenomena in the wing of a trainer aircraft and the general influence of wing sweep on critical speeds. Aeroelasticity studies the interaction between aerodynamic and elastic forces and the impact of this interaction on the aircraft's structure. There are two types of aeroelasticity: static and dynamic. The article reviews and analyzes publications related to this issue. The analysis of the research shows that when designing an aircraft, it is necessary to determine the aeroelastic characteristics of its aerodynamic surfaces. In addition to structural rigidity, the sweep angle also influences these phenomena. The scientific novelty of the study lies in the fact that, unlike the analyzed research, the designed wing structure of a trainer aircraft is considered.For the designed trainer aircraft, the critical speeds of static aeroelastic phenomena were determined. The calculation of the influence of the wing sweep angle on the divergence speeds of the trainer aircraft confirms previously obtained results regarding this influence. When the sweep is increased or decreased for wings with the same span, the torsional rigidity of the wing decreases due to the increase in the length of the line of centers of rigidity. However, the most significant impact on the aeroelastic characteristics is made by the shift of the bending center when the sweep angle changes.With forward sweep, the arm of the aerodynamic forces relative to the bending center increases, thereby reducing the critical divergence speeds. For straight sweep, as the sweep increases, the bending center moves forward, and at a certain point, the bending center is located in front of the aerodynamic center. This means that the wing twist angle decreases as the aerodynamic force increases, which, in the considered planar case, eliminates the occurrence of divergence.The preliminarily determined maximum flight speed does not exceed the critical speeds of divergence and aileron reversal. This result represents the practical value of the study. To achieve higher flight speeds, wings with straight sweep should be used. More precise computational or experimental methods for determining aeroelastic characteristics should be used in the subsequent design stages to prevent aeroelastic phenomena across the entire operational range of speeds and altitudes of the trainer aircraft.

Development of Learning Video Media in Biology Subjects

The purpose of this study is to produce valid and practical learning video media for use in the learning process. This research is a development research used to produce a product in the form of learning video media. The stages in this development include: planning stage, design stage, and development stage. The subjects in this study were 2 validators consisting of learning media experts and content or learning media material experts, 31 grade XI science students and 1 Biology subject teacher. Data collection techniques used observation, interviews, questionnaires and documentation. The data analysis techniques used were Qualitative Descriptive Analysis, and Descriptive Static Analysis. Research on this offers novelty in the form of more visual and interactive learning media, allowing students to understand complex biological concepts through interesting graphical and animated representations. In addition, these learning videos provide flexibility for students to learn independently and repeatedly, thus improving conceptual understanding and accommodating various learning styles.

SCENOGRAPHY DESIGN IN A DIRECTOR’S ARTISTIC PRACTICE

The paper describes a methodology of designing scenography for a contemporary theatrical performance in the academic process. The systematic approach to artistic visualisation of a performance, modernisation of its structure, selection of scenography functions, style and type of design widen the range of the director’s interaction with the audience as well as contributes to effective management of the creative process from the stage of the artistic concept design through to its implementation. The method of depicting compositional schemes to design action development helps individual types of art interweave with the director’s concept, develop creative thinking and cope with numerous management challenges. Designing diverse parts of staging paves the way to developing students’ skills of comprehending the processes of integration of arts and technologies. The “directing scenographic concept” method contributes to the integration of the director’s and the artist’s professional activities, helps to express a creative idea in a groundbreaking form, and turns into an effective tool of innovative design and management of a theatrical performance.

Leveraging Incremental Learning for Dynamic Modulation Recognition

Modulation recognition is an important technology used to correctly identify the modulation modes of wireless signals and is widely used in cooperative and confrontational scenarios. Traditional modulation-recognition algorithms require the assistance of expert experiences, which constrains their applications. With the rapid development of artificial intelligence in recent years, deep learning (DL) is widely advocated for intelligent modulation recognition. Typically, DL-based modulation-recognition algorithms implicitly assume a relatively static scenario in which the signal samples of all the modulation modes can be completely collected in advance. In practical situations, the radio environment is quite dynamic and the signal samples with new modulation modes may appear sequentially, in which the current DL-based modulation-recognition algorithms may require unacceptable time and computing resource consumption to re-train the optimal model from scratch. In this study, we leveraged incremental learning (IL) and designed a novel IL-based modulation-recognition algorithm that consists of an initial stage and multiple incremental stages. The main novelty of the proposed algorithm lies in the new loss function design in each incremental stage, which combines the distillation loss of recognizing old modulation modes and the cross-entropy loss of recognizing new modulation modes. With the proposed algorithm, the knowledge of the signal samples with new modulation modes can be efficiently learned in the current stage without forgetting the knowledge learned in the previous stages. The simulation results demonstrate that the proposed algorithm could achieve a recognition accuracy close to the upper bound with a much lower computing time and it outperformed the existing IL-based benchmarks.

Perancangan Multimedia Informasi Iklan Layanan Masyarakat “Domestic Abuse” Di Dinas Pemberdayaan Perempuan Perlindungan Anak Dan Keluarga Berencana Jawa Barat

Domestic abuse is a social problem in Indonesia that always be inherent and not easy to deal with, the rate of domestic abuse exploded when pandemic happen in Indonesia. in West Java alone there already 2000 case about domestic abuse that already registered. This number can be pressed if society have the courage and awareness about domestic abuse among them, as a victim or as a witness of the abuse. This multimedia application was designed for facilitate the socialization process of domestic abuse in order to cultivate courage in society to report if they see someone they know is a victim of domestic abuse. So, an information multimedia application of domestic abuse public service advertisements with a case study at the West Java Women's Empowerment, Child Protection and Family Planning Office was created. The methodology used is Multimedia Development Life Cycle (MDLC) that have 6 stages (concept, design, material collecting, assembly, testing, and distribution). The , multimedia application of domestic abuse public service advertisements was designed according to users need obtained from observation and implemented using Adobe Animate CC 2019 with Action Script 3.0 programming language.the testing of this application is using black box testing method show that this application running smoothly and fit to what the user wants. The result of this testing show that the average of the testing result from 3 category (design, feature, and user satisfaction) with 12 test parameters is 4,39 (87,8%).

Gamification for Sustainable Management Education: Prosper Management Edition's Role in South Africa's Climate Policy Engagement

The escalating climate crisis necessitates inventive strategies to engage diverse stakeholders in sustainable management and policy-making, particularly in regions like South Africa. "Prosper Management Edition," developed under the GREAT project, leverages gamification to foster communication between future corporate leaders, citizens, and policy stakeholders. This educational game connects sustainability principles with their practical application in management and policy, focusing on the integration of Sustainable Development Goals (SDGs) into business operations. This paper presents the initial design stages, implementation strategy, expected outcomes, and theoretical underpinnings of the game, aiming to enhance participants' awareness of sustainability and strategic thinking.

Enhancing DevSecOps practice with Large Language Models and Security Chaos Engineering

Recently, the DevSecOps practice has improved companies’ agile production of secure software, reducing problems and improving return on investment. However, overreliance on security tools and traditional security techniques can facilitate the implementation of vulnerabilities in different stages of the software lifecycle.. Thus, this paper proposes the integration of a Large Language Model to help automate threat discovery at the design stage and Security Chaos Engineering to support the identification of security flaws that may be undetected by security tools. A specific use case is described to demonstrate how our proposal can be applied to a retail company that has the business need to produce rapidly secure software.

Cold Coastal City Neighborhood Morphology Design Method Based on Multi-Objective Optimization Simulation Analysis

In the context of global warming and the frequent occurrence of extreme weather, coastal cities are more susceptible to the heat island effect and localized microclimate problems due to the significant influence of the oceanic climate. This study proposes a computer-driven simulation optimization method based on a multi-objective optimization algorithm, combined with tools such as Grasshopper, Ladybug, Honeybee and Wallacei, to provide scientific optimization decision intervals for morphology control and evaluation factors at the initial stage of coastal city block design. The effectiveness of this optimization strategy is verified through empirical research on typical coastal neighborhoods in Dalian. The results show that the strategy derived from the multi-objective optimization-based evaluation significantly improves the wind environment and thermal comfort of Dalian neighborhoods in winter and summer: the optimization reduced the average wind speed inside the block by 0.47 m/s and increased the UTCI by 0.48 °C in winter, and it increased the wind speed to 1.5 m/s and decreased the UTCI by 0.59 °C in summer. This study shows that the use of simulation assessment and multi-objective optimization technology to adjust the block form of coastal cities can effectively improve the seasonal wind and heat environment and provide a scientific basis for the design and renewal of coastal cities.

A numerical analysis of isolated propeller noise using a lattice Boltzmann method approach

Current environmental needs to achieve carbon neutral commercial aviation by 2050 require the development of new technologies and aircraft configurations. Among the different technological developments proposed, the use of open fan or Ultra-High Bypass Ratio configurations is of interest due to their higher propulsive efficiency and performance. To support the development of such technologies, accurate and efficient tools early in the design stages are needed to predict aerodynamic performances and noise levels. One such tool is the lattice Boltzmann method, which can perform high-fidelity aeroacoustic simulations of flows around propellers and engines. The lattice Boltzmann approach can be advantageous over other numerical methods due to its easy integration with complex geometries, its low numerical dissipation properties, and its high level of computational efficiency. This paper presents the aerodynamic and aeroacoustic numerical study of an isolated propeller using the commercial lattice Boltzmann solver ProLB. Large Eddy Simulations were carried out using a compressible hybrid thermal version of the solver. An aeroacoustic analysis using a Ffowcs-Williams and Hawkings acoustic analogy for far-field noise was carried out. The objective is to assess the capabilities of the solver to predict acoustic emissions of an isolated propeller towards the future study of an installed case.

Applying noise mapping in studying road traffic noise influence on urban blocks

With a thriving 40 years' urbanization, China cities are facing severe noise caused by road traffic that seriously influencing residents' health. To solve such environmental pollution, urban planning and design could play a significant role at the early stage. Therefore, a study on applying noise mapping simulation to mitigate road traffic noise through making proper plan and design of urban blocks is made. In the study, a rapid urbanization city, Shenzhen, was researched. Through comparing different plan parameters and design layouts, approaches benefitting mitigating road traffic noise were thoroughly investigated. It is found that bigger block size might bring forth higher noise than smaller one. The study outcomes are useful to help in creating a tranquil urban environment, particularly in urban planning & design stage.

LCV Vehicle in-cab noise prediction and reduction using SEA based simulation approach

With increase in consumer demand vehicle OEMs are developing quieter vehicles at a design stage using acoustic simulation tools to reduce development cycle times avoiding costly proto builds and test iterations. Present work describes application of statistical energy analysis (SEA) simulation approach for in cab noise prediction and noise reduction through sound package optimization for LCV vehicle. In first step complete vehicle in-cab SEA model is prepared with baseline sound package concept. It consists of comprehensive definition of structural panels, interior and exterior cavities. Noise control treatment is modelled as multi-layer poro-elastic materials. Airborne noise excitations for sources engine, transmission, intake and exhaust muffler are applied. Source strengths for above sources were derived from dyno-coupled powertrain noise tests in the anechoic chamber. Load case of rated speed was considered neglecting tire and wind noise during simulation. Contribution analysis was carried out to find out sensitivity of different panels on interior noise at various frequencies. It was observed that bottom middle floor panel and rear glass panel were major noise contributors. Noise mitigation was carried out by optimizing floor panel sound package and intake air filter within given space constraints. These modifications resulted in overall 2 dB in-cab noise reduction