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At least 217 records · Page 12

Aircraft design optimization with multidisciplinary performance criteria

The method described here for aircraft design optimization with dynamic response considerations provides an inexpensive means of integrating dynamics into aircraft preliminary design. By defining a dynamic performance index that can be added to a conventional objective function, a designer can investigate the trade-off between performance and handling (as measured by the vehicle's unforced response). The procedure is formulated to permit the use of control system gains as design variables, but does not require full-state feedback. The examples discussed here show how such an approach can lead to significant improvements in the design as compared with the more common sequential design of system and control law.

Morris, Stephen↗

Shape Optimization of Vortex Generators to Control Mack Mode Amplification

This paper demonstrates the potential to use shape optimization for the design of vortex generators in an axisymmetric boundary layer. This shape optimization increases the amplitude of stationary streaks created by streamwise vorticity, with the goal of reducing the amplification of Mack mode instabilities. The test case under consideration matches a trajectory point during the ascent phase of the HIFiRE-1 flight experiment. Wall-mounted vortex generators are added to the cone and their shape is optimized to control the amplification of Mack mode instabilities that are known to initiate laminar-turbulent transition in this flow. An empirical objective function is developed based on the previous studies of optimal streaks. A constraint on the maximum streak amplitude is added to avoid the initiation of bypass transition. The shape optimization is conducted using SU2, an open-source suite for multiphysics simulation and design. A significant improvement is observed in an integral metric of the streak amplitude, while the maximum streak amplitude is maintained close to the baseline level. The qualitative features of the optimized geometry are discussed.

Vortex generators↗

A new methodology to integrate planetary quarantine requirements into mission planning, with application to a Jupiter orbiter

A new methodology is proposed for integrating planetary quarantine objectives into space exploration planning. This methodology is designed to remedy the major weaknesses inherent in the current formulation of planetary quarantine requirements. Application of the methodology is illustrated by a tutorial analysis of a proposed Jupiter Orbiter mission. The proposed methodology reformulates planetary quarantine planning as a sequential decision problem. Rather than concentrating on a nominal plan, all decision alternatives and possible consequences are laid out in a decision tree. Probabilities and values are associated with the outcomes, including the outcome of contamination. The process of allocating probabilities, which could not be made perfectly unambiguous and systematic, is replaced by decomposition and optimization techniques based on principles of dynamic programming. Thus, the new methodology provides logical integration of all available information and allows selection of the best strategy consistent with quarantine and other space exploration goals.

Howard, R. A.↗

Performance Trend of Different Algorithms for Structural Design Optimization

Nonlinear programming algorithms play an important role in structural design optimization. Fortunately, several algorithms with computer codes are available. At NASA Lewis Research Center, a project was initiated to assess performance of different optimizers through the development of a computer code CometBoards. This paper summarizes the conclusions of that research. CometBoards was employed to solve sets of small, medium and large structural problems, using different optimizers on a Cray-YMP8E/8128 computer. The reliability and efficiency of the optimizers were determined from the performance of these problems. For small problems, the performance of most of the optimizers could be considered adequate. For large problems however, three optimizers (two sequential quadratic programming routines, DNCONG of IMSL and SQP of IDESIGN, along with the sequential unconstrained minimizations technique SUMT) outperformed others. At optimum, most optimizers captured an identical number of active displacement and frequency constraints but the number of active stress constraints differed among the optimizers. This discrepancy can be attributed to singularity conditions in the optimization and the alleviation of this discrepancy can improve the efficiency of optimizers.

Patnaik, Surya N.↗

Experimental validation of optimization-based integrated controls-structures design methodology for flexible space structures

An optimization-based integrated design approach for flexible space structures is experimentally validated using three types of dissipative controllers, including static, dynamic, and LQG dissipative controllers. The nominal phase-0 of the controls structure interaction evolutional model (CEM) structure is redesigned to minimize the average control power required to maintain specified root-mean-square line-of-sight pointing error under persistent disturbances. The redesign structure, phase-1 CEM, was assembled and tested against phase-0 CEM. It is analytically and experimentally demonstrated that integrated controls-structures design is substantially superior to that obtained through the traditional sequential approach. The capability of a software design tool based on an automated design procedure in a unified environment for structural and control designs is demonstrated.

Maghami, Peiman G.↗

Enhanced medium chain length-polyhydroxyalkanoate production by co-fermentation of lignin and holocellulose hydrolysates

Biological lignin conversion to medium chain length-polyhydroxyalkanoates (mcl-PHA) has recently emerged as an attractive alternative to petroleum-based plastics due to the renewable nature of lignin and the value-added applications of mcl-PHA. Previous reports suggested that addition of limited glucose can improve mcl-PHA accumulation in Pseudomonas putida KT2440 grown in lignin substrates. Herein, we propose a biorefinery process to systematically release lignin and sugars from lignocellulosic biomass and evaluate the potential of co-utilization of all biomass components for conversion to mcl-PHA. Our results indicate that a sequential treatment composed of acid pretreatment, enzymatic hydrolysis and alkaline treatment produces a suitable lignin stream for mcl-PHA production in engineered P. putida. In addition, the PHA titer could be increased by 71% when the lignin stream (AH) was combined with the enzymatic hydrolysate (EH) at a ratio of 75 : 25. Higher ratios of EH : AH negatively affect mcl-PHA accumulation as well as mixtures with sugars from the acid hydrolysate. The optimization of the fermentation conditions, including the inoculum (OD 600 ) and substrate (soluble solid content (SSC)), was carried out by a central composite design. The optimal conditions were achieved at OD 600 = 2.17 and SSC = 68.28 g L –1 . Under these conditions, the titer increased 4.3 fold, achieving a mcl-PHA production of 1.38 g L –1 . Lignin characterization before and after fermentation by nuclear magnetic resonance and gas chromatography showed that p-coumarates were mainly consumed during the fermentation for mcl-PHA production. Overall, this biorefinery strategy allowed us to increase mcl-PHA production by utilizing the different lignocellulosic fractions. Unlike previous studies, no model substrates were utilized at any stage of the fermentation process, representing a step forward towards process feasibility.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Layout optimization with algebraic multigrid methods

Finding the optimal position for the individual cells (also called functional modules) on the chip surface is an important and difficult step in the design of integrated circuits. This paper deals with the problem of relative placement, that is the minimization of a quadratic functional with a large, sparse, positive definite system matrix. The basic optimization problem must be augmented by constraints to inhibit solutions where cells overlap. Besides classical iterative methods, based on conjugate gradients (CG), we show that algebraic multigrid methods (AMG) provide an interesting alternative. For moderately sized examples with about 10000 cells, AMG is already competitive with CG and is expected to be superior for larger problems. Besides the classical 'multiplicative' AMG algorithm where the levels are visited sequentially, we propose an 'additive' variant of AMG where levels may be treated in parallel and that is suitable as a preconditioner in the CG algorithm.

Regler, Hans↗

Learning high-dimensional parametric maps via reduced basis adaptive residual networks

We propose a scalable framework for the learning of high-dimensional parametric maps via adaptively constructed residual network (ResNet) maps between reduced bases of the inputs and outputs. When just few training data are available, it is beneficial to have a compact parametrization in order to ameliorate the ill-posedness of the neural network training problem. By linearly restricting high-dimensional maps to informed reduced bases of the inputs, one can compress high-dimensional maps in a constructive way that can be used to detect appropriate basis ranks, equipped with rigorous error estimates. A scalable neural network learning framework is thus to learn the nonlinear compressed reduced basis mapping. Unlike the reduced basis construction, however, neural network constructions are not guaranteed to reduce errors by adding representation power, making it difficult to achieve good practical performance. Inspired by recent approximation theory that connects ResNets to sequential minimizing flows, we present an adaptive ResNet construction algorithm. This algorithm allows for depth-wise enrichment of the neural network approximation, in a manner that can achieve good practical performance by first training a shallow network and then adapting. We prove universal approximation of the associated neural network class for $L^2_v$ functions on compact sets. Our overall framework allows for constructive means to detect appropriate breadth and depth, and related compact parametrizations of neural networks, significantly reducing the need for architectural hyperparameter tuning. Numerical experiments for parametric PDE problems and a 3D CFD wing design optimization parametric map demonstrate that the proposed methodology can achieve remarkably high accuracy for limited training data, and outperformed other neural network strategies we compared against.

42 ENGINEERING↗

Self-driving thin film laboratory: autonomous epitaxial atomic-layer synthesis via real-time computer vision analysis of electron diffraction

Emerging materials science platforms with the ability to make autonomous decisions on the fly are fundamentally changing the outlook and protocols for materials optimization and discovery. Because AI-driven self-navigating schemes can effectively reduce the total number of iterations needed to arrive at the "answer" (i.e. the best stochiometric composition for a desired physical property, optimum materials processing parameters, etc.) by significant margins, they have the potential to revolutionize materials and chemical manufacturing processes at large in research laboratory settings as well as in industrial plants. Here, we demonstrate a successful implementation of real-time closed-loop autonomous navigation of a multi-dimensional materials synthesis parameter space for fabricating phase-pure epitaxial films of a metastable phase of a functional oxide in a combinatorial pulsed laser deposition chamber. Sequential epitaxial growth iterations in search of the optimized recipe to stabilize the desired crystal phase were performed using frame-by-frame quantitative computer vision analysis of reflection high-energy electron diffraction (RHEED) images of the unit-cell level film being deposited. The autonomous scheme regularly resulted in > 30-fold reduction in the number of required experiments compared to a comprehensive mapping of the parameter space. The real-time workflow developed here can be readily extended to a variety of thin film synthesis platforms opening the door for self-driving atomic-level materials design as well as autonomous optimization of semiconductor manufacturing.

36 MATERIALS SCIENCE↗

Comparative Evaluation of Different Optimization Algorithms for Structural Design Applications

Non-linear programming algorithms play an important role in structural design optimization. Fortunately, several algorithms with computer codes are available. At NASA Lewis Research Centre, a project was initiated to assess the performance of eight different optimizers through the development of a computer code CometBoards. This paper summarizes the conclusions of that research. CometBoards was employed to solve sets of small, medium and large structural problems, using the eight different optimizers on a Cray-YMP8E/8128 computer. The reliability and efficiency of the optimizers were determined from the performance of these problems. For small problems, the performance of most of the optimizers could be considered adequate. For large problems, however, three optimizers (two sequential quadratic programming routines, DNCONG of IMSL and SQP of IDESIGN, along with Sequential Unconstrained Minimizations Technique SUMT) outperformed others. At optimum, most optimizers captured an identical number of active displacement and frequency constraints but the number of active stress constraints differed among the optimizers. This discrepancy can be attributed to singularity conditions in the optimization and the alleviation of this discrepancy can improve the efficiency of optimizers.

Patnaik, Surya N.↗

Clinical practice gaps and challenges in non‐alcoholic steatohepatitis care: An international physician needs assessment

Abstract Background and aims Even as several pharmacological treatments for non‐alcoholic steatohepatitis (NASH) are in development, the incidence of NASH is increasing on an international scale. We aim to assess clinical practice gaps and challenges of hepatologists and endocrinologists when managing patients with NASH in four countries (Germany/Italy/United Kingdom/United States) to inform educational interventions. Methods A sequential mixed‐method design was used: qualitative semi‐structured interviews followed by quantitative online surveys. Participants were hepatologists and endocrinologists practising in one of the targeted countries. Interview data underwent thematic analysis and survey data were analysed with chi‐square and Kruskal‐Wallis tests. Results Most interviewees ( n = 24) and surveyed participants (89% of n = 224) agreed that primary care must be involved in screening for NASH, yet many faced challenges involving and collaborating with them. Endocrinologists reported low knowledge of which blood markers to use when suspecting NASH (56%), when to order an MRI (65%) or ultrasound/FibroScan® (46%), and reported sub‐optimal skills interpreting alanine aminotransferase (ALT, 37%) and aspartate aminotransferase (AST, 38%) blood marker test results, causing difficulty during diagnosis. Participants believed that more evidence is needed for upcoming therapeutic agents; yet, they reported sub‐optimal knowledge of eligibility criteria for clinical trials. Knowledge and skill gaps when managing comorbidities, as well as skill gaps facilitating patient lifestyle changes were reported. Conclusions Educational interventions are needed to address the knowledge and skill gaps identified and to develop strategies to optimize patient care, which include implementing relevant care pathways, encouraging referrals and testing, and multidisciplinary collaboration, as suggested by the recent Global Consensus statement on NAFLD.

Lazure, Patrice↗

SPOT Program

A Spacecraft Position Optimal Tracking (SPOT) program was developed to process Global Positioning System (GPS) data, sent via telemetry from a spacecraft, to generate accurate navigation estimates of the vehicle position and velocity (state vector) using a Kalman filter. This program uses the GPS onboard receiver measurements to sequentially calculate the vehicle state vectors and provide this information to ground flight controllers. It is the first real-time ground-based shuttle navigation application using onboard sensors. The program is compact, portable, self-contained, and can run on a variety of UNIX or Linux computers. The program has a modular objec-toriented design that supports application-specific plugins such as data corruption remediation pre-processing and remote graphics display. The Kalman filter is extensible to additional sensor types or force models. The Kalman filter design is also strong against data dropouts because it uses physical models from state and covariance propagation in the absence of data. The design of this program separates the functionalities of SPOT into six different executable processes. This allows for the individual processes to be connected in an a la carte manner, making the feature set and executable complexity of SPOT adaptable to the needs of the user. Also, these processes need not be executed on the same workstation. This allows for communications between SPOT processes executing on the same Local Area Network (LAN). Thus, SPOT can be executed in a distributed sense with the capability for a team of flight controllers to efficiently share the same trajectory information currently being computed by the program. SPOT is used in the Mission Control Center (MCC) for Space Shuttle Program (SSP) and International Space Station Program (ISSP) operations, and can also be used as a post -flight analysis tool. It is primarily used for situational awareness, and for contingency situations.

Smith, Jason T.↗

Efficient use of high performance computers for integrated controls and structures design

Simply transporting design codes from sequential-scalar computers to parallel-vector computers does not fully utilize the computational benefits offered by high performance computers. By performing integrated controls and structures design on an experimental truss platform with both sequential-scalar and parallel-vector design codes, conclusive results are presented to substantiate this claim. The efficiency of a Cholesky factorization scheme in conjunction with a variable-band row data structure is presented. In addition, the Lanczos eigensolution algorithm has been incorporated in the design code for both parallel and vector computations. Comparisons of computational efficiency between the initial design code and the parallel-vector design code are presented. It is shown that the Lanczos algorithm with the Cholesky factorization scheme is far superior to the sub-space iteration method of eigensolution when substantial numbers of eigenvectors are required for control design and/or performance optimization. Integrated design results show the need for continued efficiency studies in the area of element computations and matrix assembly.

Belvin, W. K.↗

Enhancing Building Energy Efficiency through Advanced Sizing and Dispatch Methods for Energy Storage

Energy storage and electrification of buildings hold great potential for future decarbonization. However, there are several technical and economic barriers that prevent large-scale adoption and integration of energy storage in buildings. These barriers include integration with building control systems, high capital costs, and the necessity to identify and quantify value streams for different stakeholders. To overcome these obstacles, it is crucial to develop advanced sizing and dispatch methods to assist planning and operational decision-making for integrating energy storage in buildings. This work develops simple and flexible optimal sizing and dispatch framework for thermal energy storage (TES) and battery energy storage (BES) systems in large-scale office building. The optimal sizes of TES, BES, as well as other building assets are determined in a joint manner instead of sequentially to avoid sub-optimal solutions. The interaction between the sizing at the planning stage and hourly or sub-hourly dispatch at the operating stage is explicitly modeled. The solution is determined considering both capital costs in optimal sizing and operational benefits in optimal dispatch. Comprehensive assessments are performed using simulation studies to quantify potential energy, economic, and emission benefits by different utility tariffs and climate locations, to improve our understanding of the techno-economic performance of different TES and BES systems, and to identify barriers for adopting energy storage for buildings. Finally, the proposed framework will provide guidance to a broad range of stakeholders to properly design energy storage in buildings and maximizes potential benefits, thereby advancing affordable building energy storage deployment and helping us accelerating the transition towards a cleaner and more equitable energy economy.

Yu, Mingyung↗

Computer architecture for efficient algorithmic executions in real-time systems: New technology for avionics systems and advanced space vehicles

Improvements and advances in the development of computer architecture now provide innovative technology for the recasting of traditional sequential solutions into high-performance, low-cost, parallel system to increase system performance. Research conducted in development of specialized computer architecture for the algorithmic execution of an avionics system, guidance and control problem in real time is described. A comprehensive treatment of both the hardware and software structures of a customized computer which performs real-time computation of guidance commands with updated estimates of target motion and time-to-go is presented. An optimal, real-time allocation algorithm was developed which maps the algorithmic tasks onto the processing elements. This allocation is based on the critical path analysis. The final stage is the design and development of the hardware structures suitable for the efficient execution of the allocated task graph. The processing element is designed for rapid execution of the allocated tasks. Fault tolerance is a key feature of the overall architecture. Parallel numerical integration techniques, tasks definitions, and allocation algorithms are discussed. The parallel implementation is analytically verified and the experimental results are presented. The design of the data-driven computer architecture, customized for the execution of the particular algorithm, is discussed.

Carroll, Chester C.↗

Prototype color field sequential television lens assembly

The design, development, and evaluation of a prototype modular lens assembly with a self-contained field sequential color wheel is presented. The design of a color wheel of maximum efficiency, the selection of spectral filters, and the design of a quiet, efficient wheel drive system are included. Design tradeoffs considered for each aspect of the modular assembly are discussed. Emphasis is placed on achieving a design which can be attached directly to an unmodified camera, thus permitting use of the assembly in evaluating various candidate camera and sensor designs. A technique is described which permits maintaining high optical efficiency with an unmodified camera. A motor synchronization system is developed which requires only the vertical synchronization signal as a reference frequency input. Equations and tradeoff curves are developed to permit optimizing the filter wheel aperture shapes for a variety of different design conditions.

Source record↗

Production of Designer Xylose-Acetic Acid Enriched Hydrolysate from Bioenergy Sorghum, Oilcane, and Energycane Bagasses

Xylan accounts for up to 40% of the structural carbohydrates in lignocellulosic feedstocks. Along with xylan, acetic acid in sources of hemicellulose can be recovered and marketed as a commodity chemical. Through vibrant bioprocessing innovations, converting xylose and acetic acid into high-value bioproducts via microbial cultures improves the feasibility of lignocellulosic biorefineries. Enzymatic hydrolysis using xylanase supplemented with acetylxylan esterase (AXE) was applied to prepare xylose-acetic acid enriched hydrolysates from bioenergy sorghum, oilcane, or energycane using sequential hydrothermal-mechanical pretreatment. Various biomass solids contents (15 to 25%, w/v) and xylanase loadings (140 to 280 FXU/g biomass) were tested to maximize xylose and acetic acid titers. The xylose and acetic acid yields were significantly improved by supplementing with AXE. The optimal yields of xylose and acetic acid were 92.29% and 62.26% obtained from hydrolyzing energycane and oilcane at 25% and 15% w/v biomass solids using 280 FXU xylanase/g biomass and AXE, respectively.

09 BIOMASS FUELS↗

Data for Production of Designer Xylose-Acetic Acid Enriched Hydrolysate from Bioenergy Sorghum, Oilcane, and Energycane Bagasses

Xylan accounts for up to 40% of the structural carbohydrates in lignocellulosic feedstocks. Along with xylan, acetic acid in sources of hemicellulose can be recovered and marketed as a commodity chemical. Through vibrant bioprocessing innovations, converting xylose and acetic acid into high-value bioproducts via microbial cultures improves the feasibility of lignocellulosic biorefineries. Enzymatic hydrolysis using xylanase supplemented with acetylxylan esterase (AXE) was applied to prepare xylose-acetic acid enriched hydrolysates from bioenergy sorghum, oilcane, or energycane using sequential hydrothermal-mechanical pretreatment. Various biomass solids contents (15 to 25%, w/v) and xylanase loadings (140 to 280 FXU/g biomass) were tested to maximize xylose and acetic acid titers. The xylose and acetic acid yields were significantly improved by supplementing with AXE. The optimal yields of xylose and acetic acid were 92.29% and 62.26% obtained from hydrolyzing energycane and oilcane at 25% and 15% w/v biomass solids using 280 FXU xylanase/g biomass and AXE, respectively.

Biomass Analytics↗