Reversal Design Research Articles

Analysis of Transformer GSB Bushing Fault Causes Based on Finite Element Simulation

Abstract In response to a sudden explosion and fire fault during the operation of a GSB dry-type transformer bushing in a certain power grid company, based on the structural parameters of the bushing measured by the supplier and on-site, a reverse design of the capacitor core was carried out on the faulty bushing. Based on the measured parameters and reverse design results, a finite element simulation model of the bushing electric field and structural force field was established. Calculate the electric field distribution of the casing under normal operation, 60s power frequency withstand voltage, lightning impulse, operation impulse, and other operating conditions; Conduct finite element simulation of structural mechanics to calculate the stress distribution of the casing under conditions such as cantilever load and short circuit impact; Based on the discharge traces discovered during disassembly, simulation calculations were conducted by assuming the defect situation of the casing, and the electric field distribution of the casing under different defect types was quantitatively analyzed. The simulation calculation results of the electric field under various working conditions have verified that the occurrence of this fault is the result of multiple defects working together, providing quantitative support for fault analysis and providing a certain reference for the operation and maintenance of similar casings.

Reverse vaccinology-based multi-epitope vaccine design against Indian group A rotavirus targeting VP7, VP4, and VP6 proteins

Rotavirus, a primary contributor to severe cases of infantile gastroenteritis on a global scale, results in significant morbidity and mortality in the under-five population, particularly in middle to low-income countries, including India. WHO-approved live-attenuated vaccines are linked to a heightened susceptibility to intussusception and exhibit low efficacy, primarily attributed to the high genetic diversity of rotavirus, varying over time and across different geographic regions. Herein, molecular data on Indian rotavirus A (RVA) has been reviewed through phylogenetic analysis, revealing G1P[8] to be the prevalent strain of RVA in India. The conserved capsid protein sequences of VP7, VP4 and VP6 were used to examine helper T lymphocyte, cytotoxic T lymphocyte and linear B-cell epitopes. Twenty epitopes were identified after evaluation of factors such as antigenicity, non-allergenicity, non-toxicity, and stability. These epitopes were then interconnected using suitable linkers and an N-terminal beta defensin adjuvant. The in silico designed vaccine exhibited structural stability and interactions with integrins (αvβ3 and αIIbβ3) and toll-like receptors (TLR2 and TLR4) indicated by docking and normal mode analyses. The immune simulation profile of the designed RVA multiepitope vaccine exhibited its potential to trigger humoral as well as cell-mediated immunity, indicating that it is a promising immunogen. These computational findings indicate potential efficacy of the designed vaccine against rotavirus infection.

AC-ModNet: Molecular Reverse Design Network Based on Attribute Classification.

Deep generative models are becoming a tool of choice for exploring the molecular space. One important application area of deep generative models is the reverse design of drug compounds for given attributes (solubility, ease of synthesis, etc.). Although there are many generative models, these models cannot generate specific intervals of attributes. This paper proposes a AC-ModNet model that effectively combines VAE with AC-GAN to generate molecular structures in specific attribute intervals. The AC-ModNet is trained and evaluated using the open 250K ZINC dataset. In comparison with related models, our method performs best in the FCD and Frag model evaluation indicators. Moreover, we prove the AC-ModNet created molecules have potential application value in drug design by comparing and analyzing them with medical records in the PubChem database. The results of this paper will provide a new method for machine learning drug reverse design.

A novel multi-level reverse logistics network design optimization model for waste batteries considering facility technology types

The increasing prevalence of electric vehicles (EVs) will lead to a continuous rise in the quantity of waste batteries in the future. The topic regarding reverse logistics network design (RLND) for waste batteries has garnered extensive attention from both the academic and societal realms. However, relevant research in this area has yet to delve deeper. This research proposes a mixed-integer linear programming (MILP) model to optimize the multi-level reverse logistics network (RLN) of waste batteries from the perspective of a circular economy. The model aims to minimize costs as an economic objective and to reduce carbon emissions as an environmental objective. It introduces an expected weighting factor to balance these two conflicting goals. Various technological levels are considered for different processing facilities, thereby enhancing the sustainability of the RLN. The model is applied to a numerical case study in the Nanjing Metropolitan Area of China, obtaining optimal network facility location schemes, technological configuration plans, and transportation schemes between facilities. The study emphasizes the significance of selecting different technology types for facilities, as rational process configurations effectively reduce recycling operational costs and decrease network carbon emissions. Sensitivity analysis emphasizes the impact of uncertain factors on RLND, highlighting the imperative need for a forward-thinking approach to ensure long-term sustainable development for enterprises. Managerial insights aim to guide enterprises and government departments, encouraging the adoption of higher technology types to achieve the dual goals of increased revenue and reduced carbon emissions.

Design of low delay low power hybrid logic based flip-flop using FinFET

The need for a low-power and high-speed technology for computation of digital signals is rising due to the fast growth of technological innovations. Flip-flops serve as fundamental elements in signal processing technologies. Hybrid logic has great potential for constructing flip-flop circuits because of its minimal transistor count as well as low-power properties.The present investigation presents a design for a tiny and low-power hybrid flip-flop that operates fully statically. The design has been developed by utilizing different circuitry-reduction techniques. It incorporates a hybrid logic approach combining pass transistor logic to decrease circuit complexity. The ongoing work utilizes a hybrid logic with low delay and low power to generate flip-flops. The proposed flip-flop design significantly decreases latency compared to the existing master-slave flip-flops. This flip-flop remains immune to clock overloading, resulting in reduced power consumption. Reducing the quantity of PFET (P-channel Field Effect Transistor) transistors enhances the circuit's delay, area, and power consumption. Implementing these circuit optimization techniques yields several benefits, such as reduced CLOCK-to-OUT and DIN-to-OUT node delays, decreased average power consumption, lower leakage power, and a transistor count of only 18. The results were achieved using Cadence Virtuoso at 18 nm finFET technology, with varied process corners, supply voltages ranging from 0.7 V to 1 V, and temperatures ranging from -50 °C to 75 °C. This study also presents a Monte Carlo simulation of power consumption, leakage, and delay for the suggested flip-flop. According to the simulations, the recommended flip-flop exhibits exceptional stability. The recommended flip-flop has lower power usage by at least 17.95 % compared to standard architectures due to the lower number of PFET transistors.

Prediction of the compressive mechanical properties and reverse structural design of two-dimensional mesoscopic aluminum foam based on deep learning methods

Prediction of the compressive mechanical properties and reverse structural design of two-dimensional mesoscopic aluminum foam based on deep learning methods

Multimode Photon Blockade with a Reversed Design Method

AbstractRecently, a groundbreaking advancement known as multimode photon blockade (MPB) is proposed by S. Chakram et al. [Nature. Phys. 18, 879‐884 (2022)], showcasing its ability to generate multimode W states. Inspired by their work, in this paper, an interesting method is proposed to investigate MPB by engineering the eigenstates of the system Hamiltonian, which is defined as the reverse design method. It is demonstrated that an entangled state is created with a certain probability by sharing a single photon between two coupled Kerr‐nonlinear cavities. This entangled state in the two‐coupled cavities blocks the creation of the subsequent photons. The system is in a superposition of only the entangled state and the vacuum state. And the photon blockade (PB) exists in two cavities simultaneously. The reversed design method can also be utilized to study MPB in three coupled cavities with Kerr nonlinearities by creating a three‐qubit W state.

Development of steel circularity passport: Literature review, research gaps, and program rules in New Zealand

This article conducted a systematicliterature review to find the most recent progress, barriers and opportunities in developing building material passports for structural steel reuse. To reuse steel a Circular Economy shall be implemented. A steel circular economy adoption requires the development of steel circularity passports, structural steel reusability assessment and reversible structural design. A programme rule was presented that can serves as a guideline for the development of a steel circularity passport in New Zealand. The programme rule outlined essential data and details, data resources and reliability, and steel identification process. Finally, a case study was used to demonstrate the significant benefits of applying the proposed programme rule in mitigating challenges presented by unidentified structural steel components. The 18-storey former council building has total 4,600 square meters located in Auckland downtown, New Zealand. It was found regulatory, technical, and economic barriers shall be addressed to enable steel reuse in New Zealand and presence of steel passports can facilitate steel reuse in practice by addressing the barriers in New Zealand.

High-performance coaxial reversal rotational triboelectric nanogenerator based on charge pumping strategy driving tip high voltage breakdown

Triboelectric nanogenerator (TENG) serves as an effective method for harvesting mechanical energy from the surrounding environment. Nonetheless, its practical application is hindered by issues such as inadequate charge density and wear of friction surface materials. Here, a high-performance self-supplementing coaxial inverse triboelectric nanogenerator (HSCI-TENG) based on charge pumping supplementary strategy is presented, which operates in non-contact mode and increases surface charge density with almost no friction loss. The coaxial reversal design facilitates dual-speed rotation, resulting in a significant enhancement of the output current. Furthermore, an innovative approach was employed by affixing four layers of 0.06 mm thick PET film to the storage electrode, thereby augmenting the threshold of electrode charge storage and effectively mitigating the risk of electrode breakdown. At a rotation speed of 300 rpm, the peak-to-peak voltage, peak-to-peak current, and charge transfer of HSCI-TENG are 3340 V, 360 μA and 0.97 μC, respectively. Excellent stability is demonstrated through 10000 cycle tests on the output of HSCI-TENG. In particular, the maximum output power is 770 mW at a load resistance of 8×106 Ω. The high-performance HSCI-TENG has been proven to be a stable energy source driving high voltage breakdown sensor system. The tip high voltage breakdown exhibits high frequency and continuity, with 14 breakdowns occurring within 10 seconds. Besides, HSCI-TENG has potential to serve as an energy source for high-pressure sterilization, high-pressure dust removal, and water electrolysis systems.

DNA-based ForceChrono probes for deciphering single-molecule force dynamics in living cells

Understanding cellular force transmission dynamics is crucial in mechanobiology. We developed the DNA-based ForceChrono probe to measure force magnitude, duration, and loading rates at the single-molecule level within living cells. The ForceChrono probe circumvents the limitations of invitro single-molecule force spectroscopy by enabling direct measurements within the dynamic cellular environment. Our findings reveal integrin force loading rates of 0.5-2 pN/s and durations ranging from tens of seconds in nascent adhesions to approximately 100s in mature focal adhesions. The probe's robust and reversible design allows for continuous monitoring of these dynamic changes as cells undergo morphological transformations. Additionally, by analyzing how mutations, deletions, or pharmacological interventions affect these parameters, we can deduce the functional roles of specific proteins or domains in cellular mechanotransduction. The ForceChrono probe provides detailed insights into the dynamics of mechanical forces, advancing our understanding of cellular mechanics and the molecular mechanisms of mechanotransduction.

P‐252: Late‐News Poster: Deep Learning based Inverse Design Technology for White Organic Light‐emitting Diode Thin‐film Structure

We propose a reverse design technique for WOLEDs using an artificial neural network. The inverse neural network is trained by combining forward and inverse neural networks and predicts the thin‐film structure from the out‐coupling spectrum. The predicted structures have a low error rate of less than 9 percent, demonstrating effectiveness of the inverse neural network.

Study on the Dimension Characteristics of Flexible Material TPU95A using Reverse Design and Additive Manufacturing of Automotive Parts

Study on the Dimension Characteristics of Flexible Material TPU95A using Reverse Design and Additive Manufacturing of Automotive Parts

Mathematical modeling of reverse osmosis system design and performance

ABSTRACT Reverse osmosis (RO) is one of the most effective technologies for water desalination. However, the RO system's performance is contingent on its design parameters and operating conditions. In this study, a computational model for RO desalination performance prediction was developed. The study compares the performance parameters of the RO system utilizing various types of membranes with the established model using a single pressure vessel and seven membrane elements within the pressure vessel. This study looked at two different feed water concentrations. The first is for saltwater with a concentration of 40,000 mg/L, while the second is for seawater with a concentration of 32,000 mg/L. WAVE software assessed the findings of the generated model to the recovery ratio, feed pressure, salt rejection, and permeate concentration of each membrane element inside the pressure vessel. The results of the study show good similarity between the simulation model results and the results obtained by WAVE software as they are illustrated in Figures 4–7.

Enhancing light absorption of deep ultraviolet photodiodes through intelligent algorithm-guided design of resonant nano-optical structures

The surface of the deep ultraviolet (DUV) photodiodes requires an enhanced light absorption to improve wall-plug efficiency. The resonant Mie scatterer has a high optical mode density with a high refractive index all-dielectric resonant structure, which causes strong light coupling and improves forward scattering, providing a new perspective for efficient light absorption on the surface of the DUV photodiodes. In this work, a method is proposed for the design of nano-optical structures that is capable of supporting forward light scattering across the resonant bandwidth. This is achieved by utilizing intelligent algorithms in conjunction with Maxwell’s equations. The results show that the average light absorption coefficient of the optimized optical structure is improved to more than 96% with angle-independent and polarization-independent characteristics. Based on intelligent algorithms, a reverse design approach can be employed to maximize this effect, thereby offering novel avenues for enhancing the wall-plug efficiency of the DUV photodiodes.

Reverse design and additive manufacturing of furniture protective foot covers

Reverse design and additive manufacturing technologies are fast ways to develop customised products. In this study, furniture protective foot covers were taken as the design object. Using flexible filaments of polylactic acid (PLA) and the development process of reverse design to additive manufacturing, the protective foot covers were designed and manufactured to fit the shape of the chair feet. Furniture protective foot covers have high practical value. They have a certain buffering effect, avoiding the damage caused by the collision of furniture feet with the ground when moving furniture; secondly, they reduce the noise generated by the collision of furniture feet with the ground, creating a quiet and comfortable home environment. According to the finite element simulation results, the maximum stress value of the European-style chair installed with protective foot covers was decreased by 90.8% in the case of vertical fall, which verifies that the protective foot covers have an obvious buffering effect. Noise test results show that the noise of the European-style chair installed with protective foot covers was decreased by 51.0%, which verifies that the protective foot covers have an obvious quieting effect.

Reverse design of multifunctional cascade devices based on the adjoint method

In this paper, a 1×4 ultra-compact wavelength division multiplexing cascaded device(DMC) with an arbitrary splitting ratio based on adjoint topology optimization reverse design is proposed, which is approximately two orders of magnitude smaller than that of conventional waveguide devices. It can simultaneously perform wavelength demultiplexing, mode conversion, and arbitrary ratio power splitting. The DMC separates 1310 nm and 1550 nm wavelengths, converts the input light from fundamental transverse mode (TE0) to first-order transverse mode (TE1) and second-order transverse modes (TE2), and performs arbitrarily proportional power splitting of the converted higher-order light source.

Design and Analysis of Low-Power and Area-Efficient Master-Slave Flip-Flop

In this paper, a novel master-slave flip-flop is designed that incorporates 15 transistors and a single-phase clock, employing topological and adaptive coupling methods. The proposed flip-flop circuit (PFC) is more efficient than other logic-structured flip-flops. PFC is designed using a 45 nm Complementary Metal Oxide Semiconductor (CMOS) technology node. Notably, the PFC exhibits an impressive 34.18%, 42.92%, 39.71%, 44.39%, and 46.91% improvement in average power consumption compared to the adaptive data track flip-flop (ADTFF), Hybrid Flip-Flop (HFF),18-transistor single-phase clocked (18TSPC), Logic Structured Reduction Flip-Flop (LSRFF), and Topologically compressed flip-flop (TCFF). It also improved the C to Q delay, power delay product (PDP). Monte Carlo simulations of average power and C to Q delay have been performed for 1000 samples. By reducing the number of PMOS transistors, the total area of the PFC is minimized. PFC operates effectively within a clock frequency range of up to 1 GHz.

A robust reverse pharmaceutical supply chain design considering perishability and sustainable development objectives

A robust reverse pharmaceutical supply chain design considering perishability and sustainable development objectives

Reverse optimization design of OAM sound barrier based on acoustic metamaterials

An optimized acoustic metamaterial (OAM) railway sound barrier has been designed to address the growing noise problem in railway construction. The low-frequency broadband noise attenuation is realized by an reverse design method relying on genetic algorithm-neural network (GA-NN). Simulation results show that the OAM can perfectly cover the target frequency band from 400 Hz to 1000 Hz with a bandgap ranging from 210 Hz to 1253 Hz. Compared with the initial acoustic metamaterial (IAM), the bandgap of the OAM is widened by 1295 Hz, and the sound transmission loss is improved by 15 dB. The noise reduction performance of the OAM is verified by the experiments of the fully-enclosed impedance tube and the simulation of the acoustic field modes. The acoustic experiments of the semi-enclosed OAM sound barriers show that the noise reduction of OAM sound barriers has a low-frequency broadband noise reduction effect. Compared with the existing sound barriers, the average noise reductions of OAM sound barriers in the target frequency band and bandgap range are improved to 15.9 dB and 7.8 dB, respectively.

Interactive reverse engineering of CAD models

Reverse engineering Computer-Aided Design (CAD) models based on the original geometry is a valuable and challenging research problem that has numerous applications across various tasks. However, previous approaches have often relied on excessive manual interaction, leading to limitations in reconstruction speed. To mitigate this issue, in this study, we approach the reconstruction of a CAD model by sequentially constructing geometric primitives (such as vertices, edges, loops, and faces) and performing Boolean operations on the generated CAD modules. We address the complex reconstruction problem in four main steps. Firstly, we use a plane to cut the input mesh model and attain a loop cutting line, ensuring accurate normals. Secondly, the cutting line is automatically fitted to edges using primitive information and connected to form a primitive loop. This eliminates the need for time-consuming manual selection of each endpoint and significantly accelerates the reconstruction process. Subsequently, we construct the loop of primitives as a chunked CAD model through a series of CAD procedural operations, including extruding, lofting, revolving, and sweeping. Our approach incorporates an automatic height detection mechanism to minimize errors that may arise from manual designation of the extrusion height. Finally, by merging Boolean operations, these CAD models are assembled together to closely approximate the target geometry. We conduct a comprehensive evaluation of our algorithm using a diverse range of CAD models from both the Thingi10K dataset and real-world scans. The results validate that our method consistently delivers accurate, efficient, and robust reconstruction outcomes while minimizing the need for manual interactions. Furthermore, our approach demonstrates superior performance compared to competing methods, especially when applied to intricate geometries.