Target Design Space Research Articles

Knowledge transfer accelerated turbine blade optimization via an sample-weighted variational autoencoder

The aerodynamic shape optimization (ASO) of turbine blades is a typical expensive black-box problem. With the ever increasingly strict design requirements, high-fidelity simulations are demanded, and the related simulation cost increases sharply, which means fewer simulation calls are allowed within a design optimization cycle. Then, the problem as “how to achieve better solution with fewer simulations” becomes rather crucial. Inspired by the concept of transfer learning, we propose to leverage the samples of related completed tasks (also known as source samples) to address the above problem. Specifically, an sample-weighted variational autoencoder (VAE) is proposed, which includes the source samples as part of the training dataset to boost the proportion of high-scoring solution candidates in the learnt design space of target problem, and thus increasing the probability of attaining substantially better solutions. The including of source samples in VAE training also helps to increase the accuracy of reparameterizing the source samples in target design space. Furthermore, a multi-fidelity surrogate is used to guide the optimization search, which extracts information from the source samples to help the algorithm to more quickly arrive at the small neighborhood of the true optimal of the target problem. With the above, a knowledge transfer accelerated aerodynamic shape optimization procedure is proposed for the turbine blade design, labeled as KT-ASO. Through test on a highly-loaded low-pressure turbine blade and compared against the ASO procedures without knowledge transfer, the proposed KT-ASO is shown to reduce at least 50% function calls when achieving similar optimal solutions. In the meantime, under the same sample budget, our proposed KT-ASO is shown to attain much better solutions than the compared ASO procedures.

Technical upgrade of an open-source liquid handler to support bacterial colony screening.

The optimization of genetically engineered biological constructs is a key step to deliver high-impact biotechnological applications. The use of high-throughput DNA assembly methods allows the construction of enough genotypic variants to successfully cover the target design space. This, however, entails extra workload for researchers during the screening stage of candidate variants. Despite the existence of commercial colony pickers, their high price excludes small research laboratories and budget-adjusted institutions from accessing such extensive screening capability. In this work we present COPICK, a technical solution to automatize colony picking in an open-source liquid handler Opentrons OT-2. COPICK relies on a mounted camera to capture images of regular Petri dishes and detect microbial colonies for automated screening. COPICK's software can then automatically select the best colonies according to different criteria (size, color and fluorescence) and execute a protocol to pick them for further analysis. Benchmark tests performed for E. coli and P. putida colonies delivers a raw picking performance over pickable colonies of 82% with an accuracy of 73.4% at an estimated rate of 240 colonies/h. These results validate the utility of COPICK, and highlight the importance of ongoing technical improvements in open-source laboratory equipment to support smaller research teams.

Multicomponent Droplet Drying Modeling Based on Conservation and Population Balance Equations.

The aim of this work is to present a modeling tool to describe drying kinetics and delineate evolving physical and chemical behavior of multicomponent droplets during drying. Conservation equations coupled with population balance equations (PBE) are used to achieve this goal. Modeling results are gauged with single salt-water droplet drying from literature and show congruent trends. This model is then extended to a more complex system: various droplet sizes containing methanol (solvent), Felodipine (active ingredient), and PVP (polyvinylpyrrolidone as excipient). The FIB-SEM (Focused-Ion Beam Scanning Electron Microscopy) imaging results from spray-dried particles produced with similar formulation and processing conditions are consistent with phase behavior predicted by the model. The results show competing impacts of transport phenomena on the intermittent shell formation process and final particle structure and chemical heterogeneity. Solute diffusion, solvent efflux, and intra-drop flow impact the model system. It is found that shell formation follows a fluctuating profile where the initial precipitation of the dissolved species on the droplet surface is dampened, and nucleated particles become dispersed periodically until the shell becomes strong enough to withstand internal circulations. These internal effects are dependent on droplet size and are pronounced for larger droplets. That is, the particle phase behavior and physical nature are functions of the atomized droplet size. Stemming understating from this study would inform an optimized unit, operating in target design space. This would provide better product quality control and minimize discrepancies observed in process development during the early phase vs. commercial scale.

Design Optimization of Flexure Springs for Free-Piston Stirling Engines and Experimental Evaluations with Fatigue Testing

The free-piston Stirling engine is a closed-cycle regenerative heat engine that converts heat energy into mechanical work, and requires a spring element for vibratory operations of the displacer and power pistons. In this study, the geometry of the flexural spring design was optimized through structural finite element analyses and fatigue test evaluations. First, we constructed a target design space considering the required natural frequency of the displacer spring assembly under the geometric constraints of total mass and module height. The design of experiments was employed to construct simulation cases for design factors such as the outer diameter, thickness, and number of spirals in the spring sheet. As a result, the optimized design values were obtained to satisfy the design requirements. We also fabricated a test spring specimen and conducted fatigue tests using a linear actuator system developed to have the same motion as the engine. The test results indicated that the optimized spiral spring had no fracture under operating conditions with the design piston amplitude, revealing the effectiveness of the design method.

Pareto Optimal Characterization of a Microwave Transistor

Herein, noise, gain and port mismatchings of a microwave small-signal transistor are expressed as all the set of acceptable Pareto optimal solutions and trade-off relations within the device operation ( $\text{V}_{\mathrm {DS}}$ , $\text{I}_{\mathrm {DS}}$ , $f$ ) domain without any need of expert knowledge of microwave device. In this multi-objective optimization problem, non-dominated sorting genetic algorithm (NSGA) -III is applied to an ultra-low noise amplifier (LNA) transistor NE3511S02 (HJ-FET) where the noise $\text{F}_{\mathrm {req}}\ge \text {F}_{\mathrm {min}}$ and output mismatching $\text{V}_{\mathrm {outreq}} \ge 1$ are preferred as the reference points, while the input mismatching $\text{V}_{\mathrm {inopt}} \ge 1 $ and gain $\text{G}_{\mathrm {Tmax}}$ are optimized with respect to source $\text{Z}_{\mathrm {S}}$ and load $\text{Z}_{\mathrm {L}}$ within the unconditionally stable working area. Thus, diverse set of the Pareto optimal (the required noise $\text{F}_{\mathrm {req}}$ , the optimum input $\text{V}_{\mathrm {inopt}}$ , the required output $\text{V}_{\mathrm {outreq}}$ , the maximum transducer gain $\text{G}_{\mathrm {Tmax}}$ ) quadruples are resulted from a fast search of the solution space. Furthermore, the optimum bias condition ( $\text{V}_{\mathrm {DS}}$ , $\text{I}_{\mathrm {DS}}$ ) and sensitivities of the terminations to fabrication tolerances are also determined using the cost analysis in the operation domain for the required $\text{P}_{\mathrm {max}}$ , $\text{I}_{\mathrm {DSmax}}$ and performance quadruple. Finally, this work is expected to enable a designer to provide the feasible design target space (FDTS) consisting of all trade-off relations among all the transistor’s performance ingredients to be used in the challenging LNA designs.

The Nested-Mode Power Amplifiers for Highly Efficient Multi-Octave Applications

In this article, a novel nested-mode power amplifier (NMPA) is proposed for highly efficient multi-octave applications. By introducing a group of nested guaranteed regions (GRs) at the fundamental and harmonic frequencies as the target design space, the difficulties caused by frequency overlapping in harmonically tuned multi-octave power amplifiers (PAs) can be overcome, leading to a self-consistent theory of multi-octave PAs. Furthermore, the methodology of constructing the proposed nested GRs is demonstrated based on a simplified numerical model. According to the methodology, the desired nested GRs can be constructed by following several well-defined closed-form steps. In addition, a feasible design methodology of the NMPA is established based on a simplified deembedding technique of packaged devices. Based on the proposed theory and design method, a 1–3100-MHz NMPA is designed and measured. According to the measured results, the designed PA exhibits 57.5–73.9% drain efficiency and 39–42.6-dBm output power across the band. Moreover, the linearity and linearizability of the designed NMPA are verified using up to 20-MHz-bandwidth-modulated signals across the designed band accompanied with a digital predistortion (DPD) procedure. To the best of our knowledge, this is the state-of-the-art performance of multi-octave broadband PAs.

Fuzzy Logic-Based DSE Engine: Reconfiguration for Optimization of Multicore Architectures

Moore’s law has been one of the reason behind the evolution of multicore architectures. Modern multicore architectures offer great amount of parallelism and on-chip resources that remain underutilized. This is partly due to inefficient resource allocation by operating system or application being executed. Consequently the poor resource utilization results in greater energy consumption and less throughput. This paper presents a fuzzy logic-based design space exploration (DSE) approach to reconfigure a multicore architecture according to workload requirements. The target design space is explored for L1 and L2 cache size and associativity, operating frequency, and number of cores, while the impact of various configurations of these parameters is analyzed on throughput, miss ratios for L1 and L2 cache and energy consumption. MARSSx86, a cycle accurate simulator, running various SPALSH-2 benchmark applications has been used to evaluate the architecture. The proposed fuzzy logic-based DSE approach resulted in reduction in energy consumption along with an overall improved throughput of the system.

Topology optimization for heat conduction using generative design algorithms

In this article we present a new approach to topological design for steady-state heat conduction. The method capitalizes on the use of a generative algorithm to represent topology, resulting in a decrease in the number of variables in the design description. Using a generative algorithm as a design abstraction, the optimization technique is targeted to dendritic topologies that are known to perform well for heat conduction. Specifically, a traditional topology optimization technique (SIMP) is confirmed to produce branching characteristics in optimal designs. The Space Colonization Algorithm, which can generate similar topological patterns, is selected for in-depth investigation. A genetic algorithm drives generation of design candidates, providing a highly diversified search of the target design space. Finally, several synthesized optimal designs for steady-state heat conduction, derived using the described algorithms, are compared using commercial finite element software.

A simple and efficient honey bee mating optimization approach to performance characterization of a microwave transistor for the maximum power delivery and required noise

SummaryIn this work, a simple, efficient and multi objective Honey Bee Mating Optimization (HBMO) is presented for the performance characterization of a microwave transistor to deliver maximum power to the load with the required noise Freq. Thus all the possible compatible {Freq ≥ Fmin, Vout = 1, GTmax} triplets and the corresponding source ZS and load ZL = Z*out (ZS) terminations can be obtained in the device operation domain of (VDS, IDS and f) without working analytically for the nonlinear performance and stability equations. HBMO is a recently emerging meta‐heuristic algorithm that combines the powers of the simulated annealing and genetic algorithms. Here, a microwave transistor is chosen as a case study, effectiveness and efficiency of the HBMO are shown by comparing its performance to those of the standard meta‐heuristics Genetic and Particle Swarm algorithms and the mean cost results for 10 runs are found to be 0.22, 1.65 and 1.85, respectively, for the comparable execution times. Furthermore, all the numerical results are found to agree with their analytical counterparts obtained using the microwave, linear circuit and noise theories. The Feasible Design Target Space FDTS can be built by the cross relations among all the possible compatible {Freq ≥ Fmin, Vout = 1, GTmax} triplets together their terminations {ZS, ZL = Z*out (ZS)} covering all the possible amplifier designs where both noise figure and output power are at a premium. Copyright © 2015 John Wiley & Sons, Ltd.

A comparative evaluation of multi-objective exploration algorithms for high-level design

This article presents a detailed overview and the experimental comparison of 15 multi-objective design-space exploration (DSE) algorithms for high-level design. These algorithms are collected from recent literature and include heuristic, evolutionary, and statistical methods. To provide a fair comparison, the algorithms are classified according to the approach used and examined against a large set of metrics. In particular, the effectiveness of each algorithm was evaluated for the optimization of a multiprocessor platform, considering initial setup effort, rate of convergence, scalability, and quality of the resulting optimization. Our experiments are performed with statistical rigor, using a set of very diverse benchmark applications (a video converter, a parallel compression algorithm, and a fast Fourier transformation algorithm) to take a large spectrum of realistic workloads into account. Our results provide insights on the effort required to apply each algorithm to a target design space, the number of simulations it requires, its accuracy, and its precision. These insights are used to draw guidelines for the choice of DSE algorithms according to the type and size of design space to be optimized.

A low-noise amplifier design using the performance limitations of a microwave transistor for the ultra-wideband applications

In this work, a design method of an ultra-wideband, low-noise amplifier (LNA) is put forward exploiting the performance limitations of a single high-quality discrete transistor. For this purpose, the compatible (noise F, input VSWR Vi, gain GT) triplets and their (ZS, ZL) terminations of the microwave transistor are used for the feasible design target space with the minimum noise Fmin(f), maximum gain GTmax(f), and a low constant input VSWR Vireq using the optimum noise impedance Zopt(f), and the maximum gain termination ZLmax(f) over the available bandwidth B. In the next stage, this multiobjective design process is reduced to the Darlington synthesis of the corresponding Zopt(f), ZLmax(f) terminations using the unit elements and short-circuited stubs in the T-, L-, Π-configurations. This synthesis is transformed to an optimization process with the determined feasible target space and optimization variables. Here, particle swarm intelligence is successfully implemented as a comparatively simple and efficient optimization tool in both verification of the design target space and the design process of the input and output matching circuits. Typical design examples are given with their challenging performances in the simple matching configurations realizable by the microstrip line technology. Furthermore, the performances of the synthesized amplifiers are compared using an analysis programme in MATLAB code and a microwave system simulator and verified to agree with each other and the design target space. © 2010 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2010.

Memetic optimization algorithm applied to design microwave amplifier for the specific gain value constrained by the minimum noise over the available bandwidth

In this work, the neural performance and fuzzy logic data sheets of the transistor are used to determine the feasible design target space in the optimization of a microwave amplifier. The compatible (Noise F, Input VSWR Vi, Gain GT) triplets and their (ZS, ZL) terminations of a microwave transistor are exploited for an amplifier design with the minimum noise Fmin(f), required gain GTreq(f), and a low input VSWR Vi over the available bandwidth. The multi-objective design procedure is obtained from ZS(f), ZL(f) terminations with the unit-elements and short-circuited stubs in the L+L configurations and memetic optimization algorithm is successfully implemented as an optimization tool. A typical design example is given with its challenging performance in the simple L+L configurations realizable by the microstrip line technology. © 2010 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2010.

ReSPIR: A Response Surface-Based Pareto Iterative Refinement for Application-Specific Design Space Exploration

Application-specific multiprocessor systems-on-chip (MPSoCs) are usually designed by using a platform-based approach, where a wide range of customizable parameters can be tuned to find the best tradeoff in terms of the selected figures of merit (such as energy, delay, and area). This optimization phase is called <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">design space exploration</i> (DSE), and it usually consists of a <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">multiobjective optimization</i> problem with multiple constraints. So far, several heuristic techniques have been proposed to address the DSE problem for MPSoC, but they are not efficient enough for managing the application-specific constraints and for identifying the Pareto front. In this paper, an efficient DSE methodology for application-specific MPSoC is proposed. The methodology is efficient in the sense that it is capable of finding a set of good candidate architecture configurations by minimizing the number of simulations to be executed. The methodology combines the design of experiments (DoEs) and response surface modeling (RSM) techniques for managing system-level constraints. First, the DoE phase generates an initial plan of experiments used to create a coarse view of the target design space to be explored by simulations. Then, a set of RSM techniques is used to refine the simulation-based exploration by exploiting the application-specific constraints to identify the maximum number of feasible solutions. To trade off the accuracy and efficiency of the proposed techniques, a set of experimental results for the customization of a symmetric shared-memory on-chip multiprocessor with actual workloads has been reported in this paper.

Particle swarm intelligence applied to determination of the feasible design target for a low‐noise amplifier

AbstractIn this work, feasible design target space is presented as an optimization problem for a basic low‐noise amplifier and solved by using particle swarm optimization (PSO). This feasible design space consists of {Noise Figure F, Input VSWR Vi, Gain GT} triplets and their source ZS and load ZL termination couples. Worked examples are preented for the two high technology transistor and results are compared with the ones obtained from the device performance characterization Gunes et al., IEEE Proc Circ Devices Syst 141 (1994) 337–344. Excellent agreement is observed. © 2009 Wiley Periodicals, Inc. Microwave Opt Technol Lett 51: 1214–1218, 2009; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.24276

DESIGN OF AN ULTRA-WIDEBAND, LOW-NOISE AMPLIFIER USING A SINGLE TRANSISTOR: A TYPICAL APPLICATION EXAMPLE

In this work, a design method of an Ultra-Wideband (UWB), low-noise amplifler (LNA) is proposed exerting the perfor- mance limitations of a single high-quality discrete transistor. For this purpose, the compatible (Noise F, Input VSWR Vi, Gain GT) triplets and their (ZS, ZL) terminations of a microwave transistor are exploited for the feasible design target space with the minimum noise Fmin(f), maximum gain GT max(f) and a low input VSWR Vi over the available bandwidth B. This multi-objective design procedure is reduced into syntheses of the Darlington equivalences of the ZSopt(f), ZLmax(f) terminations with the Unit-elements and short-circuited stubs in the T-, L-, ƒ-conflgurations and Particle Swarm Intelligence is successfully implemented as a comparatively simple and e-cient optimization tool into both veriflcation of the design target space and the design process of the input and output matching circuits. A typical design exam- ple is given with its challenging performance in the simple ƒ- and ƒ-conflgurations realizable by the microstrip line technology. Further- more the performances of the synthesized ampliflers are compared us- ing an analysis programme in MATLAB code and a microwave system simulator and verifled to agree with each other.

A GENERALIZED DESIGN PROCEDURE FOR A MICROWAVE AMPLIFIER: A TYPICAL APPLICATION EXAMPLE

In this work, a generalized procedure is carried out for the design of a microwave amplifier. First of all, the Performance Data Sheets (PDS) resulted from the active device characterization are used as Feasible Design Target Space (FDTS). Employing the PDS, the compatible (Noise F , Input VSWR Vi, Gain GT ) is determined over the predetermined bandwidth B between fmin and fmax operation frequencies with the source ZS and load ZL terminations as the design target. In the design stage, the Simplified Real Frequency Technique (SRFT) is utilized in the scattering-parameter formulation of the front- and back-end matching two-ports to provide the source and load terminations to the transistor, respectively. As an application example, a novel high technology transistor is chosen and the design targets are determined using the PDSs of the device and its front- and back-end matching two-ports are characterized by the scattering- parameters using the novel SRFT for each design target. Furthermore, the performances of the resulted amplifier circuits are analyzed and compared with the simulated results.

Prospects for high-gain, high yield National Ignition Facility targets driven by 2ω (green) light

The National Ignition Facility (NIF) [J. A. Paisner, E. M. Campbell, and W. J. Hogan, Fusion Technol. 26, 755 (1994)], operating at green (2ω) light, has the potential to drive ignition targets with significantly more energy than the 1.8 MJ it will produce with its baseline, blue (3ω) operations. This results in a greatly increased “target design space,” providing a number of exciting opportunities for fusion research. These include the prospect of ignition experiments with capsules absorbing energies in the vicinity of 1 MJ. This significant increase in capsule absorbed energy over the original designs at ∼150 kJ could allow high-gain, high yield experiments on NIF. This paper reports the progress made exploring 2ω for NIF ignition, including potential 2ω laser performance, 2ω ignition target designs, and 2ω laser plasma interaction studies.