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DOE OSTI2022

Revisiting Theoretical Tools and Approaches for the Valorization of Recalcitrant Lignocellulosic Biomass to Value-Added Chemicals

Biorefinery processes for converting lignocellulosic biomass to fuels and chemicals proceed via an integrated series of steps. Biomass is first pretreated and deconstructed using chemical catalysts and/or enzymes to liberate sugar monomers and lignin fragments. Deconstruction is followed by a conversion step in which engineered host organisms assimilate the released sugar monomers and lignin fragments, and produce value-added fuels and chemicals. Over the past couple of decades, a significant amount of work has been done to develop innovative biomass deconstruction and conversion processes that efficiently solubilize biomass, separate lignin from the biomass, maximize yields of bioavailable sugars and lignin fragments and convert the majority of these carbon sources into fuels, commodity chemicals, and materials. Herein, we advocate that advanced in silico approaches provide a theoretical framework for developing efficient processes for lignocellulosic biomass valorization and maximizing yields of sugars and lignin fragments during deconstruction and fuel and chemical titers during conversion. This manuscript surveys the latest developments in lignocellulosic biomass valorization with special attention given to highlighting computational approaches used in process optimization for lignocellulose pretreatment; enzyme engineering for enhanced saccharification and delignification; and prediction of the genome modification necessary for desired pathway fine-tuning to upgrade products from biomass deconstruction into value-added products. Physics-based modeling approaches such as density functional theory calculations and molecular dynamics simulations have been most impactful in studies aimed at exploring the molecular level details of solvent-biomass interactions, reaction mechanisms occurring in biomass-solvent systems, and the catalytic mechanisms and engineering of enzymes involved in biomass degradation. More recently, with ever increasing amounts of data from, for example, advanced mutli-omics experiments, machine learning approaches have begun to make important contributions in synthetic biology and optimization of metabolic pathways for production of biofuels and chemicals.

09 BIOMASS FUELS↗

NASA NTRS2003

Optimal Area Profiles for Ideal Single Nozzle Air-Breathing Pulse Detonation Engines

The effects of cross-sectional area variation on idealized Pulse Detonation Engine performance are examined numerically. A quasi-one-dimensional, reacting, numerical code is used as the kernel of an algorithm that iteratively determines the correct sequencing of inlet air, inlet fuel, detonation initiation, and cycle time to achieve a limit cycle with specified fuel fraction, and volumetric purge fraction. The algorithm is exercised on a tube with a cross sectional area profile containing two degrees of freedom: overall exit-to-inlet area ratio, and the distance along the tube at which continuous transition from inlet to exit area begins. These two parameters are varied over three flight conditions (defined by inlet total temperature, inlet total pressure and ambient static pressure) and the performance is compared to a straight tube. It is shown that compared to straight tubes, increases of 20 to 35 percent in specific impulse and specific thrust are obtained with tubes of relatively modest area change. The iterative algorithm is described, and its limitations are noted and discussed. Optimized results are presented showing performance measurements, wave diagrams, and area profiles. Suggestions for future investigation are also discussed.

Paxson, Daniel E.↗

NASA NTRS1994

CFD Optimization on Network-Based Parallel Computer System

Combining multiple engineering workstations into a network-based heterogeneous parallel computer allows application of aerodynamic optimization with advance computational fluid dynamics codes, which is computationally expensive in mainframe supercomputer. This paper introduces a nonlinear quasi-Newton optimizer designed for this network-based heterogeneous parallel computer on a software called Parallel Virtual Machine. This paper will introduce the methodology behind coupling a Parabolized Navier-Stokes flow solver to the nonlinear optimizer. This parallel optimization package has been applied to reduce the wave drag of a body of revolution and a wing/body configuration with results of 5% to 6% drag reduction.

Cheung, Samson H.↗

NASA NTRS1994

CFD Optimization on Network-Based Parallel Computer System

Cheung, Samson H.↗

NASA NTRS2017

Need for Cost Optimization of Space Life Support Systems

As the nation plans manned missions that go far beyond Earth orbit to Mars, there is an urgent need for a robust, disciplined systems engineering methodology that can identify an optimized Environmental Control and Life Support (ECLSS) architecture for long duration deep space missions. But unlike the previously used Equivalent System Mass (ESM), the method must be inclusive of all driving parameters and emphasize the economic analysis of life support system design. The key parameter for this analysis is Life Cycle Cost (LCC). LCC takes into account the cost for development and qualification of the system, launch costs, operational costs, maintenance costs and all other relevant and associated costs. Additionally, an effective methodology must consider system technical performance, safety, reliability, maintainability, crew time, and other factors that could affect the overall merit of the life support system.

Costs↗

NASA NTRS2014

Microtextured Surfaces for Turbine Blade Impingement Cooling

Gas turbine engine technology is constantly challenged to operate at higher combustor outlet temperatures. In a modern gas turbine engine, these temperatures can exceed the blade and disk material limits by 600 F or more, necessitating both internal and film cooling schemes in addition to the use of thermal barrier coatings. Internal convective cooling is inadequate in many blade locations, and both internal and film cooling approaches can lead to significant performance penalties in the engine. Micro Cooling Concepts, Inc., has developed a turbine blade cooling concept that provides enhanced internal impingement cooling effectiveness via the use of microstructured impingement surfaces. These surfaces significantly increase the cooling capability of the impinging flow, as compared to a conventional untextured surface. This approach can be combined with microchannel cooling and external film cooling to tailor the cooling capability per the external heating profile. The cooling system then can be optimized to minimize impact on engine performance.

Fryer, Jack↗

NASA NTRS2000

Multidisciplinary High-Fidelity Analysis and Optimization of Aerospace Vehicles: Formulation - Part 1

An objective of the High Performance Computing and Communication Program at the NASA Langley Research Center is to demonstrate multidisciplinary shape and sizing optimization of a complete aerospace vehicle configuration by using high-fidelity, finite element structural analysis and computational fluid dynamics aerodynamic analysis in a distributed, heterogeneous computing environment that includes high performance parallel computing. A software system has been designed and implemented to integrate a set of existing discipline analysis codes, some of them computationally intensive, into a distributed computational environment for the design of a highspeed civil transport configuration. The paper describes the engineering aspects of formulating the optimization by integrating these analysis codes and associated interface codes into the system. The discipline codes are integrated by using the Java programming language and a Common Object Request Broker Architecture (CORBA) compliant software product. A companion paper presents currently available results.

Walsh, J. L.↗

NASA NTRS1999

Optimization of Aerospace Structure Subject to Damage Tolerance Criteria

The objective of this cooperative agreement was to seek computationally efficient ways to optimize aerospace structures subject to damage tolerance criteria. Optimization was to involve sizing as well as topology optimization. The work was done in collaboration with Steve Scotti, Chauncey Wu and Joanne Walsh at the NASA Langley Research Center. Computation of constraint sensitivity is normally the most time-consuming step of an optimization procedure. The cooperative work first focused on this issue and implemented the adjoint method of sensitivity computation in an optimization code (runstream) written in Engineering Analysis Language (EAL). The method was implemented both for bar and plate elements including buckling sensitivity for the latter. Lumping of constraints was investigated as a means to reduce the computational cost. Adjoint sensitivity computation was developed and implemented for lumped stress and buckling constraints. Cost of the direct method and the adjoint method was compared for various structures with and without lumping. The results were reported in two papers. It is desirable to optimize topology of an aerospace structure subject to a large number of damage scenarios so that a damage tolerant structure is obtained. Including damage scenarios in the design procedure is critical in order to avoid large mass penalties at later stages. A common method for topology optimization is that of compliance minimization which has not been used for damage tolerant design. In the present work, topology optimization is treated as a conventional problem aiming to minimize the weight subject to stress constraints. Multiple damage configurations (scenarios) are considered. Each configuration has its own structural stiffness matrix and, normally, requires factoring of the matrix and solution of the system of equations. Damage that is expected to be tolerated is local and represents a small change in the stiffness matrix compared to the baseline (undamaged) structure. The exact solution to a slightly modified set of equations can be obtained from the baseline solution economically without actually solving the modified system. Sherrnan-Morrison-Woodbury (SMW) formulas are matrix update formulas that allow this. SMW formulas were therefore used here to compute adjoint displacements for sensitivity computation and structural displacements in damaged configurations.

Akgun, Mehmet A.↗

NASA NTRS2003

Ultra-efficient Engine Diameter Study

Engine fan diameter and Bypass Ratio (BPR) optimization studies have been conducted since the beginning of the turbofan age with the recognition that reducing the engine core jet velocity and increasing fan mass flow rate generally increases propulsive efficiency. However, performance tradeoffs limit the amount of fan flow achievable without reducing airplane efficiency. This study identifies the optimum engine fan diameter and BPR, given the advanced Ultra-Efficient Engine Technology (UEET) powerplant efficiencies, for use on an advanced subsonic airframe. Engine diameter studies have historically focused on specific engine size options, and were limited by existing technology and transportation infrastructure (e.g., ability to fit bare engines through aircraft doors and into cargo holds). This study is unique in defining the optimum fan diameter and drivers for future 2015 (UEET) powerplants while not limiting engine fan diameter by external constraints. This report follows on to a study identifying the system integration issues of UEET engines. This Engine Diameter study was managed by Boeing Phantom Works, Seattle, Washington through the NASA Glenn Revolutionary Aero Space Engine Research (RASER) contract under task order 10. Boeing Phantom Works, Huntington Beach, completed the engine/airplane sizing optimization, while the Boeing Commercial Airplane group (BCA) provided design oversight. A separate subcontract to support the overall project was issued to Tuskegee University.

Daggett, David L.↗

DOE OSTI2020

Automatic Classification of Biological Targets in a Tidal Channel Using a Multibeam Sonar

Multibeam sonars are widely used for environmental monitoring of fauna at marine renewable energy sites. However, they can rapidly accrue vast volumes of data, which poses a challenge for data processing. Here, using data from a deployment in a tidal channel with peak currents of 1–2 m s –1 , we demonstrate the data-reduction benefits of real-time automatic classification of targets detected and tracked in multibeam sonar data. First, we evaluate classification capabilities for three machine learning algorithms: random forests, support vector machines, and k-nearest neighbors. For each algorithm, a hill-climbing search optimizes a set of hand-engineered attributes that describe tracked targets. Here, the random forest algorithm is found to be most effective—in postprocessing, discriminating between biological and nonbiological targets with a recall rate of 0.97 and a precision of 0.60. In addition, 89% of biological targets are correctly classified as either seals, diving birds, fish schools, or small targets. Model dependence on the volume of training data is evaluated. Second, a real-time implementation of the model is shown to distinguish between biological targets and nonbiological targets with nearly the same performance as in postprocessing. From this, we make general recommendations for implementing real-time classification of biological targets in multibeam sonar data and the transferability of trained models.

16 TIDAL AND WAVE POWER↗

NASA NTRS2000

Adjoint Techniques for Topology Optimization of Structures Under Damage Conditions

The objective of this cooperative agreement was to seek computationally efficient ways to optimize aerospace structures subject to damage tolerance criteria. Optimization was to involve sizing as well as topology optimization. The work was done in collaboration with Steve Scotti, Chauncey Wu and Joanne Walsh at the NASA Langley Research Center. Computation of constraint sensitivity is normally the most time-consuming step of an optimization procedure. The cooperative work first focused on this issue and implemented the adjoint method of sensitivity computation (Haftka and Gurdal, 1992) in an optimization code (runstream) written in Engineering Analysis Language (EAL). The method was implemented both for bar and plate elements including buckling sensitivity for the latter. Lumping of constraints was investigated as a means to reduce the computational cost. Adjoint sensitivity computation was developed and implemented for lumped stress and buckling constraints. Cost of the direct method and the adjoint method was compared for various structures with and without lumping. The results were reported in two papers (Akgun et al., 1998a and 1999). It is desirable to optimize topology of an aerospace structure subject to a large number of damage scenarios so that a damage tolerant structure is obtained. Including damage scenarios in the design procedure is critical in order to avoid large mass penalties at later stages (Haftka et al., 1983). A common method for topology optimization is that of compliance minimization (Bendsoe, 1995) which has not been used for damage tolerant design. In the present work, topology optimization is treated as a conventional problem aiming to minimize the weight subject to stress constraints. Multiple damage configurations (scenarios) are considered. Each configuration has its own structural stiffness matrix and, normally, requires factoring of the matrix and solution of the system of equations. Damage that is expected to be tolerated is local and represents a small change in the stiffness matrix compared to the baseline (undamaged) structure. The exact solution to a slightly modified set of equations can be obtained from the baseline solution economically without actually solving the modified system.. Shennan-Morrison-Woodbury (SMW) formulas are matrix update formulas that allow this (Akgun et al., 1998b). SMW formulas were therefore used here to compute adjoint displacements for sensitivity computation and structural displacements in damaged configurations.

Akgun, Mehmet A.↗

NASA NTRS1985

X-29 initial flight test results

It is announced that the X-29 forward-swept-wing (FSW) aircraft has been built, with flight testing under way and proceeding smoothly. The X-29 is a single-seat, single-engine supersonic aircraft that blends an optimized FSW, a close-coupled near-coplar canard, an F-5A forward fuselage module employing two side-mounted engine inlets, and a new aft fuselage. An F404-GE-400 engine with afterburner provides about 16,000 lb of thrust. The X-29 was designed to be near neutrally stable in the supersonic region to minimize drag; it becomes highly unstable transonically and subsonically, which dictates the use of a computerized fly-by-wire flight control system capable of stabilizing the aircraft. The X-29 advanced technology demonstrator began flight testing on Dec. 14, 1984; by Sept. 26, 1985, its envelope had been expanded to 0.75 Mach, 350 knots estimated airspeed, and 30,000 feet altitude. The aircraft has flown with very few problems and aerodynamic, structural, and control system results have correlated well with predictions. Areas where prediction and performance are not so well correlated are noted.

Ishmael, S. D.↗

DOE OSTI2022

Floating Wind Turbine Control Optimization

We present a framework for optimizing the control parameters of floating offshore wind turbines (FOWTs). The framework combines aeroelastic simulations with a systems engineering model and control software. In an example of the optimization framework, we minimize tower damage equivalent loading with generator speed constraints. We also study the effect of thrust-limiting control and quantify the trade off between fatigue loading and energy capture using a set of optimal controller designs. Finally, we optimize the controller of four different FOWT models and compare their dynamic responses. Additional details and other use cases for the framework are presented, which can optimize different control problems and evaluate FOWT designs.

controls↗

DOE OSTI2022

An anti-PD-1–GITR-L bispecific agonist induces GITR clustering-mediated T cell activation for cancer immunotherapy

Costimulatory receptors such as glucocorticoid-induced tumor necrosis factor receptor–related protein (GITR) play key roles in regulating the effector functions of T cells. In human clinical trials, however, GITR agonist antibodies have shown limited therapeutic effect, which may be due to suboptimal receptor clustering-mediated signaling. To overcome this potential limitation, a rational protein engineering approach is needed to optimize GITR agonist-based immunotherapies. Here we show a bispecific molecule consisting of an anti-PD-1 antibody fused with a multimeric GITR ligand (GITR-L) that induces PD-1-dependent and FcγR-independent GITR clustering, resulting in enhanced activation, proliferation and memory differentiation of primed antigen-specific GITR + PD-1 + T cells. The anti-PD-1–GITR-L bispecific is a PD-1-directed GITR-L construct that demonstrated dose-dependent, immunologically driven tumor growth inhibition in syngeneic, genetically engineered and xenograft humanized mouse tumor models, with a dose-dependent correlation between target saturation and Ki67 and TIGIT upregulation on memory T cells. Anti-PD-1–GITR-L thus represents a bispecific approach to directing GITR agonism for cancer immunotherapy.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2020

Layer-Parallel Training of Deep Residual Neural Networks

Residual neural networks (ResNets) are a promising class of deep neural networks that have shown excellent performance for a number of learning tasks, e.g., image classification and recognition. Mathematically, ResNet architectures can be interpreted as forward Euler discretizations of a nonlinear initial value problem whose time-dependent control variables represent the weights of the neural network. Hence, training a ResNet can be cast as an optimal control problem of the associated dynamical system. For similar time-dependent optimal control problems arising in engineering applications, parallel-in-time methods have shown notable improvements in scalability. This paper demonstrates the use of those techniques for efficient and effective training of ResNets. The proposed algorithms replace the classical (sequential) forward and backward propagation through the network layers with a parallel nonlinear multigrid iteration applied to the layer domain. This adds a new dimension of parallelism across layers that is attractive when training very deep networks. From this basic idea, we derive multiple layer-parallel methods. The most efficient version employs a simultaneous optimization approach where updates to the network parameters are based on inexact gradient information in order to speed up the training process. Finally, using numerical examples from supervised classification, we demonstrate that the new approach achieves a training performance similar to that of traditional methods, but enables layer-parallelism and thus provides speedup over layer-serial methods through greater concurrency.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1995

Simulator Investigation of Pilot Aids for Helicopter Terminal Area Operations with One Engine Inoperative

Two recent piloted simulation experiments have investigated advanced display concepts applied to civil transport helicopter terminal area operations. Civil Category A helicopter operations apply to multi-engine helicopters wherein a safe recovery (land or fly out) is required in the event of a single engine failure. The investigation used the NASA Ames Research Center Vertical Motion Simulator, which has a full six degrees of freedom, to simulate the flight task as closely as possible. The goal of these experiments was to use advanced cockpit displays to improve flight safety and enhance the mission performance of Category A terminal area operations in confined areas. The first experiment investigated the use of military display formats to assist civil rotorcraft in performing a Category A takeoff in confined terminal areas. Specifically, it addressed how well a difficult hovering backup path could be followed using conventional instruments in comparison to panel mounted integrated displays. The hovering backup takeoff, which enables pilots to land back to the confined area pad in the event of an engine failure, was chosen since it is a difficult task to perform. Seven NASA and Army test pilots participated in the experiment. Evaluations, based on task performance and pilot workload, showed that an integrated display enabled the pilot to consistently achieve adequate or desired performance with reasonable pilot workload. Use of conventional instruments, however, frequently resulted in unacceptable performance (poor flight path tracking), higher pilot workload, and poor situational awareness. Although OEI landbacks were considered a visual task, the improved performance on the backup portion, in conjunction with increased situational awareness resulting from use of integrated displays, enabled the pilots to handle an engine failure and land back safely. In contrast, use of conventional instruments frequently led to excessive rates of sink at touchdown. A second simulation (in progress - July - August) is being conducted to investigate the use of advanced displays to perform vertical and short takeoffs and landings. One Engine Inoperative trajectories, which were optimized based on safety of flight restrictions, are utilized. Based on comments from the first experiment and further analytic development, appropriate fly out and approach guidance was added. Displays include conventional instruments with raw data, and the following integrated displays: multi-view and side-view hover displays based on the Apache Pilot Night Vision System, and variations of the pathway-in-the-sky displays with a flight-path-vector, a leader and flight director modifications. Panel mounted and head-up displays are being evaluated. Engine modifications have been incorporated to simulate 30 second and 2 minute contingency power ratings. Evaluations are based on task performance and pilot workload. NASA, Army, FAA, and industry test pilots participated. Details concerning the design, conduct, and the results of the experiment will be reported in the proposed paper.

Iseler, Laura↗

DOE OSTI2020

Spark plasma sintering (SPS) densified U 3 Si 2 pellets: Microstructure control and enhanced mechanical and oxidation properties

Dense U 3 Si 2 pellets with controlled grain structure and enhanced thermal-mechanical and oxidation properties are synthesized with spark plasma sintering (SPS). Microstructure and phase composition of the SPS densified pellets are characterized systematically using SEM, EDS, and XRD. Thermal-mechanical properties and oxidation behavior of the sintered silicide fuel pellets are analyzed by laser flash, indentation, and dynamic thermogravimetric analysis. Dense U 3 Si 2 pellets are consolidated by combining high energy ball milling and rapid sintering by SPS, and the microstructure structures are controlled from micron-sized (~5.7 μm grain size) for conventional silicide to a nanocrystalline matrix with an average grain size of ~280 nm. A dominant phase of distorted U 3 Si 2 was identified with lattice expansion due to residual thermal stress upon SPS consolidation and rapid cooling processes. Both micron-sized and nano-sized pellets show exceptional thermal transport properties, consistent with monolithic silicides reported in literature. The SPS-densified pellets possess simultaneously high hardness and fracture toughness. The SPS-densified silicide pellets also demonstrate exceptional oxidation performance with extended onset oxidation temperature above 500 °C and reduced oxidation kinetics, particularly for nano-sized pellets. A strong strain effect was proposed in which compressive stress in nano-sized pellets enhances the oxidation resistance of silicide fuels, as evidenced by the degradation of oxidation performance upon strain relaxation by isothermal annealing. The correlation among the sintering process – microstructure control – physical properties and fuel behavior is established. A new concept of strain engineering is proposed further properties optimization, enabling the development of potential oxidation and corrosion-resistant silicides with extended performance, the key technological challenge of U 3 Si 2 as the leading concept of accident tolerant fuels.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

NASA NTRS1993

Engine/airframe integration for waverider cruise vehicles

Engine-airframe integrated hypersonic waveriders have been optimized previously for both cruising flight and accelerators using inverse design flowfields to provide desirable aerodynamic performance and inlet properties. With engine installation, cruisers retain the high L/D advantages of the basic waverider form. To provide an understanding of waverider optimizer trends, an analytical development is presented which includes the presentation of a simplified model of a generic waverider shape. The model is shown to have good agreement with computational results, and it is used to demonstrate engineering tradeoffs in L/D, volume, and volume efficiency. Based on the demonstrated performance trends, and considering the desirability of uniform inlet flow, an improved waverider shape for engine-airframe integration is proposed using a hybrid cone-wedge generating flowfield.

Lewis, Mark J.↗