Miracle-dz/UniFAR-FTUs huggingface dataset:
Investigation of computational flow fields and aeroacoustic characteristics over a re-entry command module

Design and analysis of a wind tunnel model for re-entry vehicle configuration is a prolonged and expensive mission. As the aerothermodynamics loads acting on the vehicle are based on geometry, various wind tunnel models need to be built for aerodynamic characterization by experimental procedure. Alternatively, the intention of this article is to present the influence of aerodynamic and aero acoustic characteristics of a typical re-entry capsule by computational fluid dynamics analysis. A typical re-entry capsule is designed using computational design software and it is imported to a computational fluid dynamics solver and flow simulations are done at various input conditions. Stanford University unstructured computational fluid dynamics solver is used for this purpose to solve complex, multiphysics analysis, and optimization tasks. Computational fluid dynamics results are presented to understand the influence of aerodynamic characteristics of a typical re-entry capsule, by visualizing the flow field around the command module at all the flow regimes like subsonic, supersonic, and hypersonic flows. The flow fields are studied in detail and regions of high flow unsteadiness due to wake separated flow zone are identified. Aeroacoustic loading on the command module at these regions especially at shock wave zone are predicted in the present investigation with high order of accuracy.
Convolutional sparse coding‐based deep random vector functional link network for distress classification of road structures

This paper presents a convolutional sparse coding (CSC)‐based deep random vector functional link network (CSDRN) for distress classification of road structures. The main contribution of this paper is the introduction of CSC into a feature extraction scheme in the distress classification. CSC can extract visual features representing characteristics of target images because it can successfully estimate optimal convolutional dictionary filters and sparse features as visual features by training from a small number of distress images. The optimal dictionaries trained from distress images have basic components of visual characteristics such as edge and line information of distress images. Furthermore, sparse feature maps estimated on the basis of the dictionaries represent both strength of the basic components and location information of regions having their components, and these maps can represent distress images. That is, sparse feature maps can extract key components from distress images that have diverse visual characteristics. Therefore, CSC‐based feature extraction is effective for training from a limited number of distress images that have diverse visual characteristics. The construction of a novel neural network, CSDRN, by the use of a combination of CSC‐based feature extraction and the DRN classifier, which can also be trained from a small dataset, is shown in this paper. Accurate distress classification is realized via the CSDRN.
New In Situ Imaging-Based Methodology to Identify the Material Constitutive Model Coefficients in Metal Cutting Process

A great challenge of metal cutting modeling is the ability of the material constitutive model to describe the mechanical behavior of the work material under the deformation conditions that characterizes this process. In particular, metal cutting generates a large range of state of stresses, as well as strains and strain rates higher than those generated by conventional mechanical tests, including the Split-Hopkinson pressure bar tests. A new hybrid analytical–experimental methodology to identify the material constitutive model coefficients is proposed. This methodology is based on an in situ high-resolution imaging and digital image correlation (DIC) technique, coupled with an analytical model of orthogonal cutting. This methodology is particularly suitable for the identification of the constitutive model coefficients at strains and strain rates higher than those found in mechanical tests. Orthogonal cutting tests of nickel aluminum bronze alloy are performed to obtain the strains and strain rates fields in the cutting zone, using DIC technique. Shear forces derived from stress integrations are matched to the measured ones. Then, the constitutive model coefficients can be determined, which is performed by solving a sequential optimization problem. Verifications are made by comparing the strain, strain rate, and temperature fields of cutting zone from experiments against those obtained by finite element simulations using the identified material constitutive model coefficients as input.
The Need for Female Role Models in Engineering Education

The relative under-representation of women in engineering compared to their male counterparts might be related to women’s lack of self-confidence in their abilities (Felder et al., 1995), serious “academic dissatisfaction” (Adelman, cited in Brainhard, Metz, & Gillmore, 1999, p. 61), feelings of isolation (Bergvall, Sorby, & Worthen, 1994), and the uncertainty of balancing an engineering career with family life (Hynes, 1992). Studies have confirmed that females have a lower level of self-efficacy than males (Besterfield-Sacre et al., 2001; Felder et al., 1995; Zohar & Bronshtein, 2005), and because of this lack of self-confidence, females benefit from increased encouragement and validation. Demonstrating that becoming an engineer is attainable by “someone like them” (Lockwood, 2006, p. 36) might build prospective female engineers’ confidence. Determining the validity of this idea was the focus of this research study. The researcher examined whether or not strong female engineering faculty members might be a strategy to increase the admission and persistence of female engineering students. An initial focus group (N = 6) at one institution was used to create a survey that was sent to eight postsecondary institutions. Usable survey responses came from female undergraduate engineering and technology students (N = between 382 and 508, depending on the question) in their third year of study or beyond. Survey questions fell into eight categories: demographics, role model characteristics, needs in an educational environment, needs fulfilled by other people, views on the engineering education environment, level of comfort in the engineering education environment, needs from an instructor, and views of how effective scenarios might be for helping a student feel more comfortable and confident being a female in engineering. Results of data analysis suggest that female students with greater numbers of female professors have higher levels of self-confidence and worry less about how others view them.
Asymmetric Association of Resources: Conditions Under Which the Separation and Integration of Idea Generation and Implementation Support Product Innovation

This paper examines an alternative view of the use of resources in R&D teams and proposes a way to resolve the dispute between integration versus separation of idea generation and idea implementation concerning the achievement of high levels of product innovation. Contrary to the symmetric approach espoused by earlier studies, the hypotheses here are grounded in the notion that resources have an asymmetric association with idea generation and idea implementation. By asymmetric association we mean that resources have more impact on idea generation than on idea implementation. This paper considers the interactional relationship of two types of resources, time and financial budget, on idea generation and idea implementation. It is based on responses from 214 team members that belong to 40 R&D teams. The results support the existence of an asymmetric mechanism of association between resources and the idea generation and idea implementation climates. Furthermore, they demonstrate that the integration of idea generation and idea implementation is associated with high levels of product innovation when resources are available, while the separation of the two is associated with high levels of product innovation when resources are scarce.
PointAtrousNet: Point Atrous Convolution for Point Cloud Analysis

In this letter, we propose a permutation-invariant architecture—PointAtrousNet (PAN), which focuses on exploiting multi-scale local geometric details for point cloud analysis. Inspired by atrous convolution in image domains, we propose the point atrous convolution (PAC) operation. Our PAC can effectively enlarge the receptive field of filters without introducing more parameters or increasing computation amount. In particular, we propose a novel point atrous spatial pyramid pooling module to explicitly exploit neighboring contextual information at multiple scales. Moreover, local geometric details are captured by constructing neighborhood graphs in metric and feature spaces. Experimental results show that our PAN achieves state-of-the-art performance on various point cloud inference applications.
The Influence of Justice Perceptions and Affective States on Project Managers’ Responses to Client Opportunism

The contribution of psychological factors in project relationships has received limited attention. Taking the standpoint of vendor project managers, we examine their justice perceptions, affect, and consequent behavior in response to client opportunism. Data collected from 182 respondents from the information technology industry reveal that vendor project managers perceive reduced distributive and interpersonal justice, and experience lower positive and higher negative affective states, resulting in more venting and disengagement and less constructive discussion and passive acceptance. Findings suggest that psychological factors can bring about detrimental behavior in client–vendor relationships. This has long-term implications for project relationships where client opportunism occurs.
Fluid–structure interaction simulation of aortic blood flow by ventricular beating: a preliminary model for blunt aortic injuries in vehicle crashes

Abstract Blunt aortic injuries are common and severe in motor vehicle crash accidents (MVCAs), but the injury mechanisms, which can be categorised as kinematics and hydrodynamics aspects, remain to be uncertain. In this study, a finite element model was developed for the aorta-heart system with fluid–structure interaction methods, aimed to study both kinds of mechanisms simultaneously. The aortic blood flow was generated by simulating left ventricle contraction. This model was further integrated with a human body model to reconstruct a real car crash case. The aorta-heart model was validated against ventricular volume, blood pressure, velocity, flow rate and wall shear stress. The integrated model predicted aorta isthmus laceration and other injuries consistent with the case injury reports. The cardiac output during the accident was more intense than the physiological output, proving the ability of current simulation approach to capture the blood flow modification by the thoracic compressive loadings during accidents.
Aerodynamically Interacting Vertical-Axis Wind Turbines: Performance Enhancement and Three-Dimensional Flow

This study examined three-dimensional, volumetric mean velocity fields and corresponding performance measurements for an isolated vertical-axis wind turbine (VAWT) and for co- and counter-rotating pairs of VAWTs with varying incident wind direction and turbine spacings. The purpose was to identify turbine configurations and flow mechanisms that can improve the power densities of VAWT arrays in wind farms. All experiments were conducted at a Reynolds number of R e D = 7.3 × 10 4 . In the paired arrays, performance enhancement was observed for both the upstream and downstream turbines. Increases in downstream turbine performance correlate with bluff–body accelerations around the upstream turbine, which increase the incident freestream velocity on the downstream turbine in certain positions. Decreases in downstream turbine performance are determined by its position in the upstream turbine’s wake. Changes in upstream turbine performance are related to variations in the surrounding flow field due to the presence of the downstream rotor. For the most robust array configuration studied, an average 14% increase in array performance over approximately a 50° range of wind direction was observed. Additionally, three-dimensional vortex interactions behind pairs of VAWT were observed that can replenish momentum in the wake by advection rather than turbulent diffusion. These effects and their implications for wind-farm design are discussed.
Algorithmically Optimized Hemispherical Dome as a Secondary Optical Element for the Fresnel Lens Solar Concentrator

The significance of this work lies in the development of a novel code-based, detailed, and deterministic geometrical approach that couples the optimization of the Fresnel lens primary optical element (POE) and the dome-shaped secondary optical element (SOE). The objective was to maximize the concentration acceptance product (CAP), while using the minimum SOE and receiver geometry at a given f-number and incidence angle (also referred to as the tracking error angle). The laws of polychromatic light refraction along with trigonometry and spherical geometry were utilized to optimize the POE grooves, SOE radius, receiver size, and SOE–receiver spacing. Two literature case studies were analyzed to verify this work’s optimization, both with a spot Fresnel lens POE and a spherical dome SOE. Case 1 had a 625 cm2 POE at an f-number of 1.5, and Case 2 had a 314.2 cm2 POE at an f-number of 1.34. The equivalent POE designed by this work, with optimized SOE radiuses of 13.6 and 11.4 mm, respectively, enhanced the CAP value of Case 1 by 52% to 0.426 and that of Case 2 by 32.4% to 0.45. The SOE’s analytical optimization of Case 1 was checked by a simulated comparative analysis to ensure the validity of the results. Fine-tuning this design for thermal applications and concentrated photovoltaics is also discussed in this paper. The algorithm can be further improved for more optimization parameters and other SOE shapes.
Jens Rasmussen’s risk management framework

Abstract Jens Rasmussen developed a risk management framework that is extensive and multi-faceted. This framework is generally regarded as normative largely because the numerous citations of his work relate to isolated elements of that framework. There are, however, neglected elements to Rasmussen’s framework, such as functional-relational modelling, work domain analysis, and development of ecological information systems, that mark it as formative. In this article, I lay out Rasmussen’s risk management framework as gleaned from several of his publications. Rather than evaluation, the intent is to describe, and where necessary, explain his ideas. I follow with a review of AcciMap research that has been inspired by Rasmussen’s ideas. Based on that review, I conclude that Rasmussen’s formative strategy contains ideas that do not have a high profile within our current discourse on risk management. Given the limitations of a normative approach to risk management, coupled with the catastrophic potential of many of our contemporary sociotechnical systems, serious assessment of those neglected aspects of Rasmussen’s risk management framework seems warranted.
Modification of a Direct Injection Diesel Engine in Improving the Ignitability and Emissions of Diesel–Ethanol–Palm Oil Methyl Ester Blends

Blending diesel with biofuels, such as ethanol and palm oil methyl ester (PME), enhances the fuel properties and produces improved engine performance and low emissions. However, the presence of ethanol, which has a small cetane number and low heating value, reduces the fuel ignitability. This work aimed to study the effect of injection strategies, compression ratio (CR), and air intake temperature (Ti) modification on blend ignitability, combustion characteristics, and emissions. Moreover, the best composition of diesel–ethanol–PME blends and engine modification was selected. A simulation was also conducted using Converge CFD software based on a single-cylinder direct injection compression ignition Yanmar TF90 engine parameter. Diesel–ethanol–PME blends that consist of 10% ethanol with 40% PME (D50E10B40), D50E25B25, and D50E40B10 were selected and conducted on different injection strategies, compression ratios, and intake temperatures. The results show that shortening the injection duration and increasing the injected mass has no significant effect on ignition. Meanwhile, advancing the injection timing improves the ignitability but with weak ignition energy. Therefore, increasing the compression ratio and ambient temperature helps ignite the non-combustible blends due to the high temperature and pressure. This modification allowed the mixture to ignite with a minimum CR of 20 and Ti of 350 K. Thus, blending high ethanol contents in a diesel engine can be applied by advancing the injection, increasing the CR, and increasing the ambient temperature. From the emission comparison, the most suitable mixtures that can be operated in the engine without modification is D50E25B25, and the most appropriate modification on the engine is by increasing the ambient temperature at 350 K.
Dynamic simulation of a truck impact with a side entry arrester bed system

A computer simulation is conducted to investigate the performance of semitrailer entry into two different proposed side entry arrester bed systems. The proposed side entry arrester bed systems are located alongside a section of road that has variable horizontal and vertical geometry. The simulations use the same vehicle in loaded or unloaded conditions to commence a runaway descent at different speeds. To perform the computer simulations, the Bekker theory of tyre- soil interaction has been implemented. The results of each simulation are comparable graphically so that the performance of the combined road and arrester bed system can be visualised. It is found that under certain entry conditions, a side entry arrester bed could fully arrest a runaway semitrailer; however, outside of these conditions the trajectory of the semitrailer has reduced predictability. The presence of horizontal geometry needs to be analysed in detail for any side entry arrester bed. In this regard, the location of a side entry arrester bed system on the outside of a horizontal curve should be avoided. Conversely, in some circumstances, it may be acceptable to locate a side entry arrester bed system on the inside of a horizontal curve.
Design of Power- and Variability-Aware Nonvolatile RRAM Cell Using Memristor as a Memory Element

A 3 CNFETs and 2 memristors-based half-select disturbance free 3T2R resistive RAM (RRAM) cell is proposed in this paper. While the two memristors act as the nonvolatile memory elements, CNFETs are employed as high-performance switches. The proposed cell is capable of implementing bit-interleaving architecture and various error correction coding (ECC) schemes can be applied to mitigate soft-errors. The 3T2R cell has been compared with the standard 6T SRAM (S6T) and 2T2R cells. At a supply voltage of 2 V, the 3T2R cell exhibits <inline-formula> <tex-math notation="LaTeX">$7.24\times $ </tex-math></inline-formula> shorter write delay (<inline-formula> <tex-math notation="LaTeX">${T} _{\text {WA}}$ </tex-math></inline-formula>) and <inline-formula> <tex-math notation="LaTeX">$2.89\times $ </tex-math></inline-formula> lower variability in <inline-formula> <tex-math notation="LaTeX">${T} _{\text {WA}}$ </tex-math></inline-formula> than that of 2T2R. Moreover, it exhibits <inline-formula> <tex-math notation="LaTeX">$5.08\times /4.33\times $ </tex-math></inline-formula> lower variability in <inline-formula> <tex-math notation="LaTeX">${T} _{\text {RA}}$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$1.46\times 10^{7}\times /2.07\times $ </tex-math></inline-formula> lower hold power (<inline-formula> <tex-math notation="LaTeX">${H} _{\text {PWR}}$ </tex-math></inline-formula>) dissipation than that of S6T/ 2T2R at <inline-formula> <tex-math notation="LaTeX">${V} _{\text {DD}} = 2$ </tex-math></inline-formula> V. In addition, it exhibits tolerance to variations in <inline-formula> <tex-math notation="LaTeX">${V} _{\text {th}}$ </tex-math></inline-formula> of memristor while being immune to resistance-state drift and random telegraph noise (RTN)-induced instabilities during the read operation. The vastly superior characteristics of CNFET devices over MOSFETs, in combination with memristor technology, leads to such appreciable improvement in design metrics of the proposed design.
A new optical frequency transfer method via fibre based on active phase noise compensation with single acousto-optic modulator

In this paper, we propose and experimentally demonstrate a new method for optical frequency transfer over fibre. Instead of dual acousto-optic modulators (AOMs) as adopted in the traditional fibre phase noise compensation setup, here an active fibre phase noise compensation scheme with a single acousto-optic modulator (AOM) is used. The configuration simplifies the equipment of the user end while maintaining a high-performance optical frequency transfer stability. We demonstrate an actively stabilized coherent transfer at an optical frequency of 193.55THz over 10-km spooled fibre, obtaining a relative frequency stability (Allan deviation) of 3.84 × 10−16/1 s and 4.08 × 10−18/104 s, which is improved by about 2∼3 orders of magnitude in comparison with the one without any phase noise compensation that achieves a relative frequency stability of 1.81 × 10−14/1 s and 2.48 × 10−15/104 s.
Semi-Blind, Training, and Data-Aided Channel Estimation Schemes for MIMO-FBMC-OQAM Systems

This paper considers and analyzes the performance of semiblind, training, and data-aided channel estimation schemes for multiple-input multiple-output (MIMO) filter bank multicarrier (FBMC) systems with offset quadrature amplitude modulation. A semiblind MIMO-FBMC (SB-MF) channel estimator is developed that exploits both the training symbols and second-order statistical properties of the data symbols, which leads to a significant decrease in the mean squared error (MSE) with respect to its conventional training-based counterpart. Its performance is compared with that of the interference approximation method-based least squares MIMO-FBMC (LS-MF) channel estimator, wherein the channel is estimated using exclusively training symbols. The Cramér–Rao lower bounds are derived to characterize the MSE of the proposed and LS-MF estimators, which interestingly demonstrate that while the MSE per parameter of the proposed scheme decreases with the number of receive antennas, it remains constant for the training-based scheme. The resulting bit error rates are derived for the proposed SB-MF and LS-MF channel estimators. An expectation maximization-based data-aided MIMO-FBMC channel estimator is also investigated that performs iterative maximum a posteriori channel estimation in the E-step followed by data detection in the M-step. A comparative analysis is presented for the computational complexities of the various schemes. Simulation results with practical channel models demonstrate that the proposed semiblind scheme significantly outperforms the training-based and data-aided schemes.