Conventional Design Research Articles

Transfer-Learning-Enhanced Regression Generative Adversarial Networks for Optimal eVTOL Takeoff Trajectory Prediction

Electric vertical takeoff and landing (eVTOL) aircraft represent a crucial aviation technology to transform future transportation systems. The unique characteristics of eVTOL aircraft include reduced noise, low pollutant emission, efficient operating cost, and flexible maneuverability, which in the meantime pose critical challenges to advanced power retention techniques. Thus, optimal takeoff trajectory design is essential due to immense power demands during eVTOL takeoffs. Conventional design optimizations, however, adopt high-fidelity simulation models in an iterative manner resulting in a computationally intensive mechanism. In this work, we implement a surrogate-enabled inverse mapping optimization architecture, i.e., directly predicting optimal designs from design requirements (including flight conditions and design constraints). A trained inverse mapping surrogate performs real-time optimal eVTOL takeoff trajectory predictions with no need for running optimizations; however, one training sample requires one design optimization in this inverse mapping setup. The excessive training cost of inverse mapping and the characteristics of optimal eVTOL takeoff trajectories necessitate the development of the regression generative adversarial network (regGAN) surrogate. We propose to further enhance regGAN predictive performance through the transfer learning (TL) technique, creating a scheme termed regGAN-TL. In particular, the proposed regGAN-TL scheme leverages the generative adversarial network (GAN) architecture consisting of a generator network and a discriminator network, with a combined loss of the mean squared error (MSE) and binary cross-entropy (BC) losses, for regression tasks. In this work, the generator employs design requirements as input and produces optimal takeoff trajectory profiles, while the discriminator differentiates the generated profiles and real optimal profiles in the training set. The combined loss facilitates the generator training in the dual aspects: the MSE loss targets minimum differences between generated profiles and training counterparts, while the BC loss drives the generated profiles to share analogous patterns with the training set. We demonstrated the utility of regGAN-TL on optimal takeoff trajectory designs for the Airbus A3 Vahana and compared its performance against representative surrogates, including the multi-output Gaussian process, the conditional GAN, and the vanilla regGAN. Results showed that regGAN-TL reached the 99.5% generalization accuracy threshold with only 200 training samples while the best reference surrogate required 400 samples. The 50% reduction in training expense and reduced standard deviations of generalization accuracy achieved by regGAN-TL confirmed its outstanding predictive performance and broad engineering application potential.

ECHO: Energy-Efficient Computation Harnessing Online Arithmetic—An MSDF-Based Accelerator for DNN Inference

Deep neural network (DNN) inference demands substantial computing power, resulting in significant energy consumption. A large number of negative output activations in convolution layers are rendered zero due to the invocation of the ReLU activation function. This results in a substantial number of unnecessary computations that consume significant amounts of energy. This paper presents ECHO, an accelerator for DNN inference designed for computation pruning, utilizing an unconventional arithmetic paradigm known as online/most significant digit first (MSDF) arithmetic, which performs computations in a digit-serial manner. The MSDF digit-serial computation of online arithmetic enables overlapped computation of successive operations, leading to substantial performance improvements. The online arithmetic, coupled with a negative output detection scheme, facilitates early and precise recognition of negative outputs. This, in turn, allows for the timely termination of unnecessary computations, resulting in a reduction in energy consumption. The implemented design has been realized on the Xilinx Virtex-7 VU3P FPGA and subjected to a comprehensive evaluation through a rigorous comparative analysis involving widely used performance metrics. The experimental results demonstrate promising power and performance improvements compared to contemporary methods. In particular, the proposed design achieved average improvements in power consumption of up to 81%, 82.9%, and 40.6% for VGG-16, ResNet-18, and ResNet-50 workloads compared to the conventional bit-serial design, respectively. Furthermore, significant average speedups of 2.39×, 2.6×, and 2.42× were observed when comparing the proposed design to conventional bit-serial designs for the VGG-16, ResNet-18, and ResNet-50 models, respectively.

Aeroelastic analysis of a lightweight topology-optimized sandwich panel

Sandwich structures with lattice cores are novel, lightweight composite structures and are widely used in the aerospace industry. Besides, the aeroelastic behavior of sandwich panels in a supersonic flow regime still needs to be thoroughly studied. This work investigates the supersonic flutter of a sandwich panel whose core is topology-optimized. A finite element model of a sandwich panel based on the layerwise theory, coupled with the first-order piston theory, is presented. The sandwich panel core is assessed using a topology optimization approach with flutter loading constraints. The subsequent analytical homogenization scheme is developed to provide the equivalent mechanical properties of the topology-optimized panel. The modeling approach is fully validated, and the results demonstrate that the sandwich panel is capable of enlarging the flutter-free operational flight range when compared with other conventional panel designs. A parametric analysis of the topology-optimized sandwich panel regarding the critical flutter conditions is performed.

Enhanced FPGA linear phase FIR filter with amalgam multiplier

ABSTRACT Designing high-performance integrated circuits that balance area, speed, and power is increasingly challenging. This study optimises hardware implementation of FIR filters using an innovative Amalgam Multiplier, minimising resource use without compromising performance. The key challenge in designing signal processing hardware is the multiplier design, which significantly affects efficiency. This study explores integrated circuit optimisation, addressing the delicate balance between area utilisation, speed, and power consumption. Focusing on hardware implementation of Finite Impulse Response (FIR) filters in signal processing, the article starts with a conventional FIR filter design using a standard array multiplier which consumed 1.790 W, with 8 s real-time completion. Then, Linear Phase FIR (LP-FIR) filter is designed using Braun and Dadda Multiplier. LP-FIR filter with Braun multiplier consumed 1.436 W power and 26 s of completion time whereas LP-FIR with Dadda multiplier consumed 1.363 W power and 23 s of completion time. Finally, the implementation of novel LP-FIR enhanced by Amalgam multiplier consumed 0.302 W power and 10.29 s of completion time, marking a significant advancement in integrated circuit design.

An Efficient Design of 2-BIT Arithmetic Logical Unit in Quantum Dot Cellular Automata

For the past two decades, CMOS technology has reigned supreme in the world of Very Large Scale Integration (VLSI). But Quantum Dot Cellular Automata (QCA) is stepping into the spotlight, offering a fresh solution to the growing challenges of CMOS. This paper delves into the potential of QCA circuits by presenting a 2-bit Arithmetic Logic Unit (ALU) crafted with this groundbreaking technology, while also benchmarking it against conventional CMOS designs. The proposed QCA-based ALU delivers a trifecta of benefits: streamlined circuit design, exceptional space efficiency, and reduced quantum cost—all while keeping performance sharp in terms of latency and area usage. This 2-bit ALU encompasses a suite of operations: addition, subtraction, multiplication, division, bitwise AND, OR, XOR, and XNOR. QCA technology addresses some of CMOS's major pain points, like slow switching speeds, and doesn't require additional power sources, making it both efficient and environmentally friendly. This is not just an incremental improvement; it's a bold leap into the future of circuit design

Automated intelligent design of modified uni-traveling carrier photodectors

This paper introduces an automatic intelligent design method for the modified uni-traveling carrier photodetector (MUTC-PD). The conventional photodetector design process often relies on the numerical solution of complex nonlinear partial differential equations to simulate and optimize device performance, which is not only computationally intensive but also inefficient. To overcome this challenge, we apply the charge control principle to calculate the photodetector bandwidth, which improves the computational speed by a factor of approximately 1800 compared to the numerical solution of nonlinear partial differential equations. To further optimize the structure of the photodetector, we incorporate the Velocity Varying Climbing Particle Swarm Optimization (VVCPSO) algorithm. This is an improved algorithm based on the traditional particle swarm algorithm, which is able to quickly find the optimal solution in a complex parameter space. By applying the VVCPSO algorithm, we successfully fine-tuned the photodetector structure and obtained structural parameters with optimal performance. Our thorough verification process confirms that the proposed method is consistent with the results of ATLAS simulation software. Automated design has resulted in a high-performance MUTC-PD with a responsivity of 0.52A/W and a bandwidth of 60 GHz (@-3 V) at a mesa diameter of 16µm. Compared to the pre-optimized device, the bandwidth is increased to three times the original. By reducing the mesa diameter to 4µm, the bandwidth can be further increased to 82 GHz (@-3 V). The proposed method's calculation speed is fast enough, enabling extensive parameter studies to optimize device performance.

Responding to the real problem of sustainable resuscitation skills with real assessment. Mixed-methods evaluation of an authentic assessment programme.

The retention of resuscitation skills is a widespread concern, with a rapid decay in competence frequently following training. Meanwhile, training programmes continue to be disconnected with real-world expectations and assessment designs remain in conflict with the evidence for sustainable learning. This study aimed to evaluate a programmatic assessment pedagogy which employed entrustment decision and the principles of authentic and sustainable assessment (SA). We conducted a prospective sequential explanatory mixed methods study to understand and address the sustainable learning challenges faced by final-year undergraduate paramedic students. We introduced a programme of five authentic assessments based on actual resuscitation cases, each integrating contextual elements that featured in these real-life events. The student-tutor consensus assessment (STCA) tool was configured to accommodate an entrustment scale framework. Each test produced dual student led and assessor scores. Students and assessors were surveyed about their experiences with the assessment methodologies and asked to evaluate the programme using the Ottawa Good Assessment Criteria. Eighty-four students participated in five assessments, generating dual assessor-only and student-led results. There was a reported mean score increase of 9% across the five tests and an 18% reduction in borderline or below scores. No statistical significance was observed among the scores from eight assessors across 420 unique tests. The mean student consensus remained above 91% in all 420 tests. Both student and assessor participant groups expressed broad agreement that the Ottawa criteria were well-represented in the design, and they shared their preference for the authentic methodology over traditional approaches. In addition to confirming local sustainability issues, this study has highlighted the validity concerns that exist with conventional resuscitation training designs. We have successfully demonstrated an alternative pedagogy which responds to these concerns, and which embodies the principles of SA, quality in assessment practice, and the real-world expectations of professionals.

Accelerate vaccine development using seamless phase 2/3 trial designs

ABSTRACT Background Traditional vaccine development, often a lengthy and costly process of three separated phases. However, the swift development of COVID-19 vaccines highlighted the critical importance of accelerating the approval of vaccines. This article showcases a seamless phase 2/3 trial design to expedite the development process, particularly for multi-valent vaccines. Research Design and Methods This study utilizes simulation to compare the performance of seamless phase 2/3 design with that of conventional trial design, specifically by re-envisioning a 9-valent HPV vaccine trial. Across three cases, several key performance metrics are evaluated: overall power, type I error rate, average sample size, trial duration, the percentage of early stop, and the accuracy of dose selection. Results On average, when the experimental vaccine was assumed to be effective, the seamless design that performed interim analyses based solely on efficacy saved 555.73 subjects, shortened trials by 10.29 months, and increased power by 3.70%. When the experimental vaccine was less effective than control, it saved an average of 887.73 subjects while maintaining the type I error rate below 0.025. Conclusion The seamless design proves to be a compelling strategy for vaccine development, given its versatility in early stopping, re-estimating sample sizes, and shortening trial durations.

Bioinspired H-Bonding Connected Gradient Nanostructure Actuators Based on Cellulose Nanofibrils and Graphene.

The construction of flexible actuators with ultra-fast actuation and robust mechanical properties is crucial for soft robotics and smart devices, but still remains a challenge. Inspired by the unique mechanism of pinecones dispersing seeds in nature, a hygroscopic actuator with interlayer network-bonding connected gradient structure is fabricated. Unlike most conventional bilayer actuator designs, the strategy leverages biobased polyphenols to construct strong interfacial H-bonding networks between 1D cellulose nanofibers and 2D graphene oxide, endowing the materials with high tensile strength (172MPa) and excellent toughness (6.64MJm-3). Furthermore, the significant difference in hydrophilicity between GO and rGO, along with the dense interlayer H-bonding, enables ultra-fast water exchange during water absorption and desorption processes. The resulted actuator exhibits ultra-fast driving speed (154°s-1), excellent pressure-resistant and cyclic stability. Taking advantages of these benefits, the actuator can be fabricated into smart devices (such as smart grippers, humidity control switches) with significant potential for practical applications. The presented approach to constructing interlayer H-bonding in gradient structures is instructive for achieving high performance and functionalization of biomass nanomaterials and the complex of 1D/2D nanomaterials.

Numerical and experimental analysis of a cross-finned solar receiver for parabolic dish collectors

A parabolic dish solar collector (PDC) is used to concentrate solar radiation on a receiver to produce hot water or steam for various thermal applications. The solar receiver of the PDC is one of the significant components to improve the overall efficiency of the PDC. The present study is a numerical and experimental investigation of the thermal performance of a solar receiver with vertical fins with and without cross fins. The fin orientation was investigated using 0.056 kg/s, 0.083 kg/s, and 0.111 kg/s water flow rates. COMSOL Multiphysics® was used to simulate the receiver to determine the receiver’s temperature behavior. The thermal performance parameters such as heat gain, heat loss, convective heat transfer coefficient, and thermal, and exergy efficiency were analyzed under various flow conditions. The cross fins effectively prolong the water residence, increasing turbulence, and heat transfer and reducing heat loss to the surroundings. The receiver with cross fins at higher flow rate conditions shows higher thermal performance than lower flow rate and without fins conditions. The solar radiation during the outdoor testing is in a range of 300–950 W/m2 and the ambient temperature varies from 30-37 °C. The peak average thermal and exergy efficiency obtained for the cross-finned receiver at 0.111 kg/s is 64.4 %, and 6.3 %, respectively. Cross-finned receiver operating at 0.111 kg/s reduced CO2 mitigation rate, estimated at approximately 0.29 tons of CO2 per year, along with a lower carbon credit gain at $0.47. Thus, the proposed cross-fin solar receiver demonstrates improved thermoeconomic performance than conventional receiver designs, offering a more cost-effective design with minimal investment.

Experimental validation of auxetic stent designs: three-point bending of 3D printed Titanium prototypes

Experimental validation of auxetic stent designs: three-point bending of 3D printed Titanium prototypes

A domain knowledge-informed design space exploration methodology for mechanical layout design

Layout designs have a large number of design variables and various physical constraints. Conventional design exploration approaches are time-consuming and may require human intervention. A unique feature about physical layout designs is the availability of domain knowledge, which can be utilised to speed up the design process. In this paper, we propose a generative deep learning-based design space exploration (DSE) methodology that is capable of learning design constraints in the layout design without explicit supervision. Moreover, it can incorporate domain knowledge in the generated layouts, thereby speeding up the design process. This is realised by constructing a layout generation variational autoencoder (LGVAE) model, which uses a latent space as an interface to generate the layouts. By training the LGVAE model, significantly lower-dimensional representations can be learned compared to the original dimensionality of the design space. Therefore, the number of design variables is greatly reduced. We showcase the performance of the proposed DSE approach by solving the heat source layout design problem encountered in thermal management of chips. Experiments demonstrate that the LGVAE model is capable of generating compressed latent representations that capture the characteristics of the input samples, which makes the DSE cost-effective.

A novel tree -like bionic structure for liquid-cooled lithium-ion battery plates

To maintain the optimal operating temperature range for the power batteries of new energy vehicles, this paper proposes a novel tree-structured channel cold plate. An orthogonal experimental approach was employed to investigate the effects of inlet flow rate m, inlet channel quantity n, channel width d, and hierarchy ratio α on battery temperatures Tmax, standard temperature difference Tσ, and pressure drop ΔP. Non-dominated sorting genetic algorithm II (NSGA-II) was utilized to obtain an optimized solution set. The results reveal that the tree-like cold plate configuration including m = 15 g/s, n = 7 and 8, d = 3 mm, and α = 1:2:1 demonstrates superior performance. Thus, the developed cold plate was further compared with the conventional straight-through cold plate design. The results indicate that the proposed tree-like cold plate exhibits the maximum decreases of 13.94% in Tmax, 52.94% in Tσ, and 61.5% in ΔP. The most significant improvement in the composite indicator PEC was 89%. In conclusion, the tree-like channel cold plate developed in this study provides excellent heat dissipation capability for power batteries, offering valuable insights for the thermal design of battery liquid cooling systems.

Design and optimization of heat dissipation for a high-voltage control box in energy storage systems

Abstract To address the issue of excessive temperature rises within the field of electronic device cooling, this study adopts a multi-parameter optimization method. The primary objective is to explore and realize the design optimization of the shell structure of the high voltage control box, aiming to effectively mitigate the temperature rise in internal components and enhance their thermal management efficacy without altering the fan performance, environmental conditions, or spatial layout. Initially, the study employs computational fluid dynamics methods to investigate the heat dissipation characteristics of the high voltage control box, subsequently verifying the simulation parameters' accuracy through temperature rise tests. Building upon this foundation, the article conducts a thorough analysis of how the position and shape of the box's openings impact the device's temperature rise. The findings suggest that configuring circular openings on the front and rear sides can optimize the heat dissipation effect. Moreover, the SHERPA algorithm was employed to refine the size and distribution of the openings on the outer shell of the high voltage control box through multi-parameter optimization, yielding locally optimal structural parameters. Post-optimization, the temperature measurement points within the high voltage control box exhibited a maximum reduction in temperature rise of 27.16%. The pivotal contribution of this methodology is the application of a data-driven decision-making process for the enhancement of conventional heat dissipation designs. This research offers invaluable practical insights and novel perspectives on the optimization of thermal management designs for box-type electronic devices.

Development and Performance of an Adaptive Adfreeze Pile

Field studies and geothermal modelling shows ground cooling below raised buildings in permafrost regions significantly offsets the ground warming impact of climate warming. For an adfreeze pile, the ground cooling below a raised building improves the capacity relative to pre-construction conditions. Many designers do not take credit for this cooling effect but propose to incorporate thermal mitigation in the design, such as the use of thermopiles. The adaptive adfreeze pile is an innovative concept that accounts for long-term cooling beneath raised buildings and the resulting enhanced pile capacity. The concept entails the installation of a closed ended steel pipe as a conventional adfreeze pile. If future ground temperatures warm above a design threshold, a small diameter thermosyphon could be inserted into the interior of the hollow pile. The retrofitted thermosyphon, if ever required, would passively cool the ground during winter to reduce the mean annual ground temperature and maintain pile capacity. This approach is cost-effective compared to conventional thermopile design and provides greater thermosyphon performance assurances in the long-term. This paper details of the application of this pile design for two, multi-story buildings in Old Crow Yukon, and describes the geothermal background showing its technical feasibility and initial performance data.

Multilayer lensless camera for improving the condition number

Computational lensless imaging technology implements the thinning of the optical system by replacing optical imaging with image reconstruction processing. The conventional optical design uses a single coded mask and an image sensor; however, researchers have recently proposed optical designs incorporating multiple stacked coded apertures for multidimensional and wide-field imaging. Here, we investigate the effects of multilayering the coded aperture on the performance of two-dimensional spatial imaging. Through simulations and optical experiments, we demonstrate that multilayering the coded aperture enhances the condition number of the optical system’s transmission matrix and consequently improves the accuracy of image reconstruction in lensless imaging.

Wide Voltage Swing Potentiostat with Dynamic Analog Ground to Expand Electrochemical Potential Windows in Integrated Microsystems.

Electrochemical measurements are vital to a wide range of applications such as air quality monitoring, biological testing, food industry, and more. Integrated circuits have been used to implement miniaturized and low-power electrochemical potentiostats that are suitable for wearable devices. However, employing modern integrated circuit technologies with low supply voltage precludes the utilization of electrochemical reactions that require a higher potential window. In this paper, we present a novel circuit architecture that utilizes dynamic voltage at the working electrode of an electrochemical cell to effectively enhance the supported voltage range compared to traditional designs, increasing the cell voltage range by 46% and 88% for positive and negative cell voltages, respectively. In return, this facilitates a wider range of bias voltages in an electrochemical cell, and, therefore, opens integrated microsystems to a broader class of electrochemical reactions. The circuit was implemented in 180 nm technology and consumes 2.047 mW of power. It supports a bias potential range of 1.1 V to -2.12 V and cell potential range of 2.41 V to -3.11 V that is nearly double the range in conventional designs.

Damping effects of a stay cable attached with a viscous damper and a high damping rubber damper considering cable bending stiffness and damper support flexibility

To mitigate cable oscillations in cable-stayed bridges, a common approach involves using a strategically positioned viscous damper near the cable’s anchorage and bridge deck. However, for longer cables, this method may be insufficient due to installation constraints. In such cases, supplementing the damping system with a high-damping rubber (HDR) damper near the cable’s anchorage point on the bridge tower becomes imperative to enhance the cable’s damping ratio. Conventional designs often overlook crucial factors like viscous damper support stiffness and stay cable bending stiffness when integrating dampers into cable-stayed structures. This study presents findings on achieving an effective damping ratio in stay cables by using both a viscous damper and an HDR damper, considering the influence of viscous damper support stiffness and stay cable bending stiffness. The results indicate that the combined deployment of these dampers achieves a damping efficiency approximately equivalent to the sum of their individual effects. Importantly, decreased viscous damper support stiffness significantly affects the damping effectiveness, leading to a rapid decline in the stay cable’s damping ratio. While stay cable bending stiffness also influences the damping ratio, its impact is relatively less pronounced than that of viscous damper support stiffness. The study outcomes enable a more accurate prediction of the achievable damping ratio for a stay cable with additional components, considering both damper support stiffness and stay cable bending stiffness. Furthermore, the study explores parameters of both the viscous damper and HDR damper, such as the viscous coefficient, loss coefficient, HDR damper stiffness, and damper placement, evaluating their influence on the first damping ratio of the stay cable. The survey results provide valuable insights for determining optimal parameters for both dampers, maximizing the damping efficiency of cable-stayed bridges.

Modification of impeller blades for the efficient mixing of particulate suspensions in a stirred tank

The fractal arrangement of perforated holes were introduced in the impeller blades for the suspension of solid particles in a stirred tank. The mixing characteristics of solid-liquid two phases in a stirred tank with a fractal arrangement perforated impeller (FAP impeller) were investigated. Results indicated that incorporating fractal arranged perforated holes in the impeller blades resulted in a reduction in power consumption (P) compared to conventional designs under the same agitation speed. Moreover, a rise in the iteration quantity of fractal arranged perforated holes in impeller blades resulted in higher power consumption and power number, but still lower than those observed with conventional designs. FAP impeller enhanced turbulent intensity, increased shear effect on the fluid, minimized trailing vortex dimension behind the impeller blades, and promoted the axial circulation of solid particles, ultimately leading to the better suspension quality of solid particles compared to pitched blade impeller at the constant P. The above phenomena became increasingly evident as the iteration number in the fractal arranged perforated holes in the FAP impeller blades increased.

Cut layout optimization for design of kirigami metamaterials under large stretching

Kirigami metamaterials have gained increasing attention due to their unusual mechanical properties under large stretching. However, most metamaterial designs obtained with trial-and-error approaches tend to lose their desirable properties under large tensile strains due to occurrence of instability caused by out-of-plane buckling. To cope with this limitation, this paper presents a systematic approach of cut layout optimizing for designing kirigami metamaterials working at large tensile strains by fully exploiting their out-of-plane buckling behaviors. This method can also mitigate the local stress concentration issue at the hinges of conventional kirigami designs working at in-plane deformation modes. The effectiveness of the proposed method is demonstrated through several examples regarding metamaterial design with negative Poisson's ratio and specified flip angle pattern. It is shown that the proposed method is capable of addressing the highly nonlinear deformation impacts on the mechanical performance under large stretching, to meet the growing and diverse demands in the field of kirigami metamaterials.