Powerful Design Approach Research Articles

Research on Low-Power Digital Integrated Circuit Technology

In today’s diverse and rapidly developing field of low-power technologies, various industries are actively applying these advanced technologies to practical production in order to reduce energy consumption and mitigate environmental pollution. Based on this core concept, this article delves into and compares the principles, advantages, and disadvantages of the low-power technology of passive tag chips with the representative low-power technologies of dual-power and crossed-zero clocking, as well as their respective application areas. Specifically, the article conducts a detailed comparative analysis of the low-power technology of passive tag chips versus dual-power and crossed-zero clocking technologies from three perspectives: power consumption, design approach, and practical application. Through in-depth research, it was found that the low-power technology of passive tag chips holds significant advantages in the logistics industry, making it particularly well-suited for this field; meanwhile, dual-power and crossed-zero clocking technologies perform better in high-performance computing, making them more appropriate for such an application environment.

Classification and quantitative characterisation of the excited states of π-conjugated diradicals.

Diradicals are of high current interest as emerging materials for next generation optoelectronic applications. To tune their excited-state properties it would be greatly beneficial to have a detailed understanding of the wave functions of the different states involved but this endeavour is hampered by formal and practical barriers. To tackle these challenges, we present a formal analysis as well as concrete results on diradical excited states. We start with a detailed investigation of the available states of a two-orbital two-electron model viewed from both the valence-bond and molecular orbital perspectives. We highlight the presence of diradical and zwitterionic states and illustrate their connections to the states found in closed-shell molecules. Subsequently, we introduce practical protocols for analysing states from realistic multireference computations applying these to the para-quinodimethane (pQDM) molecule. The analysis reveals four different categories of states - diradical, zwitterionic, HOMO-SOMO as well as biexciton - while also providing insight into their energetics and optical properties. Twisting the CH2 groups allows us to interconvert between the closed- and open-shell forms of pQDM illustrating the connection between the states in both forms. More generally, we hope that this work will lay the foundations for a more powerful rational design approach to diradicals for photophysical applications.

Blade Design and Aerodynamic Performance Analysis of a 20 MW Wind Turbine for LCoE Reduction

The aim of this study is to develop a blade mass model that incorporates a low-induction rotor (LIR) and a low-specific power concept to reduce aerodynamic loads and lower the Levelized Cost of Energy (LCoE). This blade mass model replaces the traditional simple scaling rule and incorporates the concept of LCoE reduction, presenting not only the mass distribution in the blade span direction but also the stiffness distribution. In order to achieve the desired reduction in LCoE, we developed a mathematical model that expresses blade mass as a function of the axial induction factor, which influences the aerodynamic load on the blade. We used this model to determine geometries of various low-induction rotors for 20 MW class horizontal axis wind turbine, and to identify the axial induction factor that correlates with the lowest blade mass. The chord length and twist angle in the spanwise direction of the blade were determined using PROPID’s reverse design process, based on the specified axial induction factor. Since the low-induction concept is not aerodynamically optimal, a low-specific power design approach was also adopted. This involved increasing the blade length and shifting the power curve to the left. By doing so, the AEP is increased, directly contributing to a reduction in the LCoE. Mass per unit length of the blade was presented, reflecting the distribution of airfoil type, blade geometry, and shapes of internal structures such as spars and webs.

Refactoring with domain-driven design in an industrial context

ContextSoftware developers need to constantly work on evolving the structure and the stability of the code due to changing business needs of the product. There are various refactoring approaches in industry which promise improvements over source code composition and maintainability.ObjectiveIn our research, we want to improve the maintainability of an existing system through refactoring using Domain-Driven Design (DDD) as a software design approach. We also aim for providing empirical evidence on its effect on maintainability and the challenges as perceived by developers.MethodIn this study, we applied the action research methodology, which facilitates close academia-industry collaboration and regular presence in the studied product. We utilized focus groups to discover problems of the existing system with a qualitative approach. We reviewed the subject codebase to construct our own expert opinion as well and identified problems in the codebase and matched them with the ones raised by engineers in the team. We refactored the existing software system according to DDD principles. To measure the effects of our actions, we utilized Technology Acceptance Model (mTAM) questionnaire, and also semi-structured interviews with the development team for data collection, and card sorting methodology for qualitative analysis. For minimizing bias that might affect our results with the existing software engineers in the team, we extended our measurement with three new joiner software engineers in the team through the think aloud protocol.ResultsWe have identified that engineers mostly gave positive answers to our interview questions, which are mapped to software maintainability metrics defined by ISO/IEC 25010. Our DDD refactoring scored 85 in PU and 83 in PEU, leading to an overall mTAM score of 84. This means acceptable on the acceptability scale, B on the grade scale, and good on the adjective rating scale.ConclusionOur research led us to conclude that a powerful design approach, like DDD, is an effective tool for restructuring and resolving software issues in this situation. It offers standardization to the software and the refactoring efforts. We realized that DDD entails a certain degree of complexity and cognitive load, which is a barrier for software engineers, but they are aware of its benefits.

Problematizing constructive alignment in higher education in gulf cooperation council countries

ABSTRACT Constructive alignment (CA) has developed into one of the most significant concepts in higher education since its establishment in the late 1990s. CA is a powerful instrument for curriculum design that aligns learning outcomes with teaching and learning activities and assessments to enhance the quality of students’ learning. In this conceptual study, Foucault’s concept of problematization is used as the theoretical framework to explain how and why CA has become a powerful approach for curriculum design dominantly used in higher education worldwide. The discussion focuses on three main blind spots of the CA: pedagogical hegemony, implementation fidelity, and policy enactment. The study closes by offering concluding thoughts and identifying new agendas for research.

Designing Geometric Degrees of Freedom in ReO3‐Type Coordination Polymers

AbstractEngineering the interplay of structural degrees of freedom that couple to external stimuli such as temperature and pressure is a powerful approach for material design. New structural degrees of freedom expand the potential of the concept, and coordination polymers as a chemically versatile material platform offer fascinating possibilities to address this challenge. Here, we report a new class of perovskite‐like AB2X6 coordination polymers based on a [BX3] − ReO3‐type host network ([Mn(C2N3)3] −), in which the spatial orientation of divalent A2+ cations ([R3N(CH2)nNR3]2+) with separated charge centers that bridge adjacent ReO3‐cavities is introduced as a new geometric degree of freedom. Herringbone and head‐to‐tail order pattern of [R3N(CH2)nNR3]2+ cations are obtained by varying the separator length n and, together with distortions of the pseudocubic [BX3] − network, they determine the materials’ stimuli‐responsive behavior such as counterintuitive large negative compressibility and uniaxial negative thermal expansion. This new family of coordination polymers highlights the chemists’ capabilities of designing matter on a molecular level to address macroscopic material functionality and underpins the opportunities of the design of structural degrees of freedom as a conceptual framework for rational material synthesis in the future.

Interfacial self-assembled Si@SiOX@C microclusters with high tap density for high-performance Li-ion batteries

Despite the silicon (Si) anode having a high mass theoretical capacity, the critical volume change and pulverization problems of the Si particles must be overcome by the powerful nanomaterial design approach. However, the large surface area and low tap density of nanomaterials severely weaken the capacity advantage of Si at the electrode level. Herein, we design a stable self-assembled microcluster as the anode of Li-ion batteries based on nanostructured core-shell Si@SiOX building blocks to achieve high tap density (0.67 g cm−3). The high-viscosity gel as a carbon source is prepared by vacuum esterification to form a carbon skeleton and a carbon layer inside and outside the microcluster, respectively. In the self-assembled microclusters, the carbon layer acts as a micron-size electrolyte barrier to promote the formation of a stabilizing Li+ permeable solid-electrolyte interphase (SEI) layer, the carbon skeleton and the SiOX layer provide a buffer for the volume expansion of silicon. As expected, this structure shows an excellent specific capacity of 1063 mAh cm−3 (1586 mAh/g) at 0.2 A/g and an excellent cycling stability (1042 mAh/g after 500 cycles at 0.7 A/g).

Cysteine derivatives as acetyl lysine mimics to inhibit zinc-dependent histone deacetylases for treating cancer.

Zinc-dependent histone deacetylases (HDACs) are important epigenetic regulators that have become important drug targets for treating cancer. Although five HDAC inhibitors have been approved for treating several cancers, there is still a huge demand on discovering new HDAC inhibitors to explore the therapeutic potentials for treating solid tumor cancers. Substrate mimics are a powerful rational design approach for the development of potent inhibitors. Here we describe the rational design, synthesis, biological evaluation, molecular docking and invivo efficacy study of a class of HDAC inhibitors using Nε-acetyl lysine mimics that are derived from cysteine. As a result, compounds 7a, 9b and 13d demonstrated pan-HDAC inhibition and broad cytotoxicity against several cancer cell lines, comparable to the approved HDAC inhibitor SAHA. Furthermore, 13d significantly inhibited tumor growth in a A549 xenograft mice model without any obvious weight loss, supporting that the cysteine-derived acetyl lysine mimics are promising HDAC inhibitors with therapeutic potentials for treating cancer.

A Survey on Low Power Design Approaches in Nanoscale Regime

Background: The increased demand for battery operated portable systems boost up the field of low power VLSI design. Integrated circuits are enhancing the performance of the systems in terms of lesser area requirement, higher functionality, and faster response at lower technology nodes. The applied power supply and the threshold voltage of the individual device are scaled down at lower technology node. Scaling of the threshold voltage of the devices raises the issue of leakage current. Objective: Leakage current should be made recessive with the continuous scaling of technology nodes. Methods: Various leakage current mitigation methods had been employed to reduce the leakage current at different abstraction levels. This review paper demonstrates the survey of systematic arrangement of device scaling, leakage power, its causes, and various methods to overcome the leakage current at circuit level design. Results: 3 input NAND (NAND3) gate is designed and simulated at 22 nm technology node on HSPICE tool and analyzed for comparison of different leakage reduction techniques. Conclusion: INDEP approach is the most effective approach to reduce the leakage current and to improve the reliability of the circuits followed by DTCMOS technique as compared to other available techniques.

Rapid airfoil design optimization via neural networks-based parameterization and surrogate modeling

Aerodynamic optimization based on computational fluid dynamics (CFD) is a powerful design approach because it significantly reduces the design time compared with the human manual design. However, CFD-based optimization can still take hours to converge because it requires repeatedly running computationally expensive flow simulations. To further shorten the design optimization time, we propose a fast, interactive design framework that allows us to complete an airfoil aerodynamic optimization within a few seconds. This framework is made efficient through a B-spline-based generative adversarial network model for shape parameterization, which filters out unrealistic airfoils for a reduced design space that contains all relevant airfoil shapes. Moreover, we use a combination of multilayer perceptron, recurrent neural networks, and mixture of experts for surrogate modeling to enable both scalar (drag and lift) and vector (pressure distribution) response predictions for a wide range of Mach numbers (0.3 to 0.7) and Reynolds numbers (104 to 1010). To verify our proposed framework, we compare the optimization results with the ones computed by direct CFD-based optimization for subsonic and transonic conditions. The results show that the optimal designs and the aerodynamic quantities (lift, drag, and pressure distribution) obtained by our proposed framework agree well with the ones computed by direct CFD-based optimizations and evaluations. The proposed framework is being integrated into a web-based interactive aerodynamic design framework that allows users to predict drag, lift, moment, pressure distribution, and optimal airfoil shapes for a wide range of flow conditions within seconds.

Reliability-Based Design Optimization of Microstructures With Analytical Formulation

Microstructures are stochastic by their nature. These aleatoric uncertainties can alter the expected material performance substantially and thus they must be considered when designing materials. One safe approach would be assuming the worst case scenario of uncertainties in design. However, design under the worst case conditions can lead to over-conservative solutions that provide less effective material properties. Here, a more powerful design approach can be developed by implementing reliability constraints into the optimization problem to achieve superior material properties while satisfying the prescribed design criteria. This is known as reliability-based design optimization (RBDO), and it has not been studied for microstructure design before. In this work, an analytical formulation that models the propagation of microstructural uncertainties to the material properties is utilized to compute the probability of failure. Next, the analytical uncertainty solution is integrated into the optimization problem to define the reliability constraints. The presented optimization under uncertainty scheme is exercised to maximize the yield stress of α-Titanium and magnetostriction of Galfenol, respectively.

A Realization Method for Transforming a Topology Optimization Design into Additive Manufacturing Structures

Topology optimization is a powerful design approach that is used to determine the optimal topology in order to obtain the desired functional performance. It has been widely used to improve structural performance in engineering fields such as in the aerospace and automobile industries. However, some gaps still exist between topology optimization and engineering application, which significantly hinder the application of topology optimization. One of these gaps is how to interpret topology results, especially those obtained using the density framework, into parametric computer-aided design (CAD) models that are ready for subsequent shape optimization and manufacturing. In this paper, a new method for interpreting topology optimization results into stereolithography (STL) models and parametric CAD models is proposed. First, we extract the skeleton of the topology optimization result in order to ensure shape preservation and use a filtering method to ensure characteristics preservation. After this process, the distribution of the nodes in the boundary of the topology optimization result is denser, which will benefit the subsequent curve fitting. Using the curvature and the derivative of curvature of the uniform B-spline curve, an adaptive B-spline fitting method is proposed in order to obtain a parametric CAD model with the fewest control points meeting the requirement of the fitting error. A case study is presented to provide a detailed description of the proposed method, and two more examples are shown to demonstrate the validity and versatility of the proposed method.

Evolutionary design for energy-efficient approximate digital circuits

Energy and computation efficiency are of the major concerns in ever-growing embedded systems. Approximate computing as a new design methodology trades precision for energy efficiency. Evolutionary algorithms as an optimization approach would explore the possible space of the solution to find the best and efficient solutions and hence, are compatible with approximate computing objectives. This paper exploits Cartesian Genetic Programming (CGP) as a powerful design approach to bring novel and newfound approximate solutions. Our contributions are twofold: First, proposing a new simple yet effective seeding approach for CGP which decreases the evolution time and computational effort and also increases the precision of the resulted evolved circuits. Second, proposing an offline pre-evolution approach in order to reduce the complexity of design and hence, make it possible to use CGP for designing more complex problems. The results of evolving arithmetic benchmarks show improvement of the proposed seeding technique both in precision of evolved circuits and also the required computational effort. Also, exploiting the pre-evolution approach for multiplier benchmark reduce the size of truth tables over 94% and not only make it possible to use CGP to design larger multipliers, but also breaks down the power delay product (PDP) parameter more than 65% in compression with some state of the art approximate and exact multipliers.

Ultra low power design approach of asynchronous delta sigma modulator

Asynchronous Delta Sigma Modulator (ADSM) is assuming an extremely vital part in the majority of conveying device and information convertor and in this manner requires the exceptional consideration in outlining. The execution of the vast majority of the device having DSM as an essential segment is described by the execution of the DSM hardware. This paper introduces the audit of work performed in planning of Asynchronous Delta Sigma Modulator. Latest trends are about the utilization of ADSM for various applications. Contrasting the execution of various ADSM circuits, an execution paradigm is settled for ADSM plan. The execution criteria basically think about the Low working voltages, low power utilization, high SNDR and better focus recurrence. At that point a strategy is suggested that characterizes the High execution ADSM that influence joined utilization of various methods to like inverse operation and mass driven MOS for ultra low power outline and enhancing the execution of an Asynchronous Delta Sigma Modulator.

Pseudo-peptide amyloid-β blocking inhibitors: molecular dynamics and single molecule force spectroscopy study

By combining MD simulations and AFS experimental technique, we demonstrated a powerful approach for rational design and single molecule testing of novel inhibitor molecules which can block amyloid-amyloid binding – the first step of toxic amyloid oligomer formation. We designed and tested novel pseudo-peptide amyloid-β (Aβ) inhibitors that bind to the Aβ peptide and effectively prevent amyloid-amyloid binding. First, molecular dynamics (MD) simulations have provided information on the structures and binding characteristics of the designed pseudo-peptides targeting amyloid fragment Aβ (13−23). The binding affinities between the inhibitor and Aβ as well as the inhibitor to itself have been estimated using Umbrella Sampling calculations. Atomic Force Spectroscopy (AFS) was used to experimentally test several proposed inhibitors in their ability to block amyloid-amyloid binding – the first step of toxic amyloid oligomer formation. The experimental AFS data are in a good agreement with theoretical MD calculations and demonstrate that three proposed pseudo-peptides bind to amyloid fragment with different affinities and all effectively prevent Aβ-Aβ binding in similar way. We propose that the designed pseudo-peptides can be used as potential drug candidates to prevent Aβ toxicity in Alzheimer's disease.

A Novel Paradigm to Eliminate Timing Violations using AHL

Objectives: This Paper presents a novel low power design approach for multipliers to eliminate timing violations. There are two major issues which are concentrated in this paper are positive bias temperature instability and negative bias temperature instability. Both the things affect the speed of transistor and leads to timing violations, which intern leads to the failure of an entire system. Methods: In this work, bypassing multiplier is used with adaptive hold logic. The implementation is done in 180 nm deep submicron CMOS technology. Findings: power consumption and error rate is studied after employing the AHL. Improvements: The experimental result shows that the performance of multipliers with AHL improved 72.8% when compared to existing methods and consumes less power.

Structural topology optimization considering connectivity constraint

Topology optimization has been regarded as a powerful design approach for determining optimal topology of a structure to obtain desired functional performances within a defined design domain. Considering manufacturing process constraints in topology optimization becomes increasingly important due to its potential practical applications. In this paper, we propose a novel topology optimization model with manufacturing process related connectivity constraints. A generalized method, named as virtual scalar field method (VSFM), is developed for describing and enforcing desired connectivity constraint. As an illustrative example, the connectivity constraint can be converted to an equivalent maximum temperature constraint when temperature is chosen as the scalar field. The temperature constraint is then easily integrated and implemented in routine topology optimization. The simply-connected constraint, which excludes interior closed cavities and is representative of many advanced manufacturing techniques, e.g. additive manufacturing (AM) or casting, is used as an example to demonstrate the key ideas and the efficiency of the VSF method. Some numerical examples, which consider the connectivity constraint in topology optimization, are presented to show the validity of this method.

Free material optimization for laminated plates and shells

Free Material Optimization (FMO) is a powerful approach for conceptual optimal design of composite structures. The design variable in FMO is the entire elastic material tensor which is allowed to vary almost freely over the design domain. The imposed requirements on the tensor are that it is symmetric and positive semidefinite. Most of today's studies on FMO focus on models for two- and three-dimensional structures. The objective of this article is to extend existing FMO models and methods to laminated plate and shell structures, which are used in many engineering applications. In FMO, the resulting optimization problem is generally a non convex semidefinite program with many matrix inequalities which requires special-purpose optimization methods. The FMO problems are efficiently solved by a primal-dual interior point method developed and implemented by the authors. The quality of the proposed FMO models and the method are supported by several large-scale numerical experiments.

Using Shainin DOE for Six Sigma: an Indian case study

Shainin design of experiments (DOE) offers a powerful and effective experimental design approach for solving the chronic quality problems that plague manufacturers worldwide. However, the academic literature still contains a few empirical studies on the use of non-statistical Shainin DOE tools to simplify the quality improvement initiatives. In order to overcome this deficiency, this case describes framework for incorporating Shainin experimental design within Six Sigma define–measure–analyse–improve–control and tests its effectiveness in an Indian automotive gear manufacturing unit. Shainin tools such as Paired Comparison, Product/Process search, Concentration chart, B vs. C analysis, Pre-control chart were employed to analyse, improve and control the gear manufacturing process. The study provides stimulus for the wider application of Shainin experimental design approach for industrial experimentation.

Design and implementation of a passive UHF RFID tag with a temperature and process compensation oscillator

A fully integrated passive UHF RFID tag chip compatible with ISO18000-6B protocol is pre- sented. In order to save die area, an all CMOS transistor regulator is adopted. An NMOS based traditional Dickson rectifier is employed with the advantage of circuit simplicity. An ultra-low power ring oscillator with temperature and process compensation is designed to guarantee the accuracy of the clock, which has a direct impact on the accuracy of backscatter link frequency (BLF). By utilizing several low power design approaches, a low power baseband processor is achieved. The whole tag chip is fabricated in TSMC 0.18m CMOS technology and the chip size is 730m × 605m. Measurement results show that the total power consumption of the tag is about 7W with a sensitivity of −13.1 dBm and an operational range of about 7.5 m under 4 W effective isotropic radiated (EIRP) power, and the accuracy of BLF is within ±10%. With the long operational range, the tag is suitable for many commercial applications, such as supply-chain and logistics managements as well as location sensing system.