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At least 433 records · Page 24

The Role of Formal Experiment Design in Hypersonic Flight System Technology Development

Hypersonic airbreathing engine (scramjet) powered vehicles are being considered to replace conventional rocket-powered launch systems. Effective utilization of scramjet engines requires careful integration with the air vehicle. This integration synergistically combines aerodynamic forces with propulsive cycle functions of the engine. Due to the highly integrated nature of the hypersonic vehicle design problem, the large flight envelope, and the large number of design variables, the use of a statistical design approach in design is effective. Modern Design-of-Experiments (MDOE) has been used throughout the Hyper-X program, for both systems analysis and experimental testing. Application of MDOE fall into four categories: (1) experimental testing; (2) studies of unit phenomena; (3) refining engine design; and (4) full vehicle system optimization. The MDOE process also provides analytical models, which are also used to document lessons learned, supplement low-level design tools, and accelerate future studies. This paper will discuss the design considerations for scramjet-powered vehicles, specifics of MDOE utilized for Hyper-X, and present highlights from the use of these MDOE methods within the Hyper-X Program.

McClinton, Charles R.↗

Microstructure Modeling of 3rd Generation Disk Alloy

The objective of this initiative, funded by NASA's Aviation Safety Program, is to model, validate, and predict, with high fidelity, the microstructural evolution of third-generation high-refractory Ni-based disc superalloys during heat treating and service conditions. This initiative is a natural extension of the DARPA-AIM (Accelerated Insertion of Materials) initiative with GE/Pratt-Whitney and with other process simulation tools. Strong collaboration with the NASA Glenn Research Center (GRC) is a key component of this initiative and the focus of this program is on industrially relevant disk alloys and heat treatment processes identified by GRC. Employing QuesTek s Computational Materials Dynamics technology and PrecipiCalc precipitation simulator, physics-based models are being used to achieve high predictive accuracy and precision. Combining these models with experimental data and probabilistic analysis, "virtual alloy design" can be performed. The predicted microstructures can be optimized to promote desirable features and concurrently eliminate nondesirable phases that can limit the reliability and durability of the alloys. The well-calibrated and well-integrated software tools that are being applied under the proposed program will help gas turbine disk alloy manufacturers, processing facilities, and NASA, to efficiently and effectively improve the performance of current and future disk materials.

Jou, Herng-Jeng↗

Advances in the Lightweight Air-Liquid Composite Heat Exchanger Development for Space Exploration Applications

An advanced, lightweight composite modular Air/Liquid (A/L) Heat Exchanger (HX) Prototype for potential space exploration thermal management applications was successfully designed, manufactured, and tested. This full-scale Prototype consisting of 19 modules, based on recommendations from its predecessor Engineering Development unit (EDU) but with improved thermal characteristics and manufacturability, was 11.2 % lighter than the EDU and achieves potentially a 42.7% weight reduction from the existing state-of-the-art metallic HX demonstrator. However, its higher pressure drop (0.58 psid vs. 0.16 psid of the metal HX) has to be mitigated by foam material optimizations and design modifications including a more systematic air channel design. Scalability of the Prototype design was validated experimentally by comparing manufacturability and performance between the 2-module coupon and the 19-module Prototype. The Prototype utilized the thermally conductive open-cell carbon foam material but with lower density and adopted a novel high-efficiency cooling system with significantly increased heat transfer contact surface areas, improved fabricability and manufacturability compared to the EDU. Even though the Prototype was required to meet both the thermal and the structural specifications, accomplishing the thermal requirement was a higher priority goal for this first version. Overall, the Prototype outperformed both the EDU and the corresponding metal HX, particularly in terms of specific heat transfer, but achieved 93.4% of the target. The next generation Prototype to achieve the specification target, 3,450W would need 24 core modules based on the simple scaling factor. The scale-up Prototype will weigh about 14.7 Kg vs. 21.6 Kg for the metal counterpart. The advancement of this lightweight composite HX development from the original feasibility test coupons to EDU to Prototype is discussed in this paper.

Shin, E. Eugene↗

Characterization of Low-Temperature, Co-Fired Ceramic-Manufactured Electrostatic Thruster-Closeout Report

The goal of the project was to evaluate prototypes of an experimental thruster developed by the University of Arkansas (UA), Fayetteville, AR. The design under evaluation is a radio frequency (RF) electrostatic thruster that was fabricated using the low-temperature, co-fired ceramic (LTCC) materials and fabrication process. This materials system is analogous to printed circuit board (PCB) technology with the most significant difference being that the laminate is replaced by a ceramic material and the copper layer is replaced by printed sinterable silver paste. LTCC designs are baked after fabrication and assembled to realize an entirely monolithic structure with internal conductors, vias, and cavities. In this process, the LTCC electrostatic thruster (LTCC-ET) that is the subject of the present work becomes a monolithic ceramic thruster capable of withstanding temperatures in excess of 500 ºC. The UA and NASA Marshall Space Flight Center (MSFC) jointly performed prototype testing on the LTCC-ET under a NASA Cooperative Agreement Notice (CAN) award. The LTCC-ET was tested at MSFC in May 2018 over a 1-week period. There were two goals for the test program: (1) Testing to determine the operating parameters required to create plasma ignition in the test articles. This was explored by setting a propellant flowrate and increasing RF power until plasma ignition was observed. Testing was conducted with both argon and krypton. (2) Investigate the thrust and specific impulse (Isp) performance of the thruster as a function of propellant flowrate and grid voltage. This goal was not met during the project as technical challenges in maintaining stable plasma ignition arose due to stress and heating of the RF power feed. In summary, a prototype thruster design (consisting of three packaged units) was fabricated by UA and tested for the first time under vacuum conditions at MSFC to experimentally determine basic performance metrics and functionality. It was found that the design was not sufficiently optimized or robust enough in its initial iteration to support a significant test campaign or characterization program. It was concluded that the propellant outlet channels must be reduced in size with the flowpaths adjusted to increase propellant residence time in the thruster, and that the RF connector must be replaced with a version capable of handling higher power throughput and heating. However, even in its unoptimized form, a plasma could be produced in the LTCCET, demonstrating the efficacy of the design approach. The design is especially compelling due to its low cost to manufacture and, more importantly, its scalability of size and power throughput. Low cost and scalability are also important in that additional functionalities, such as thrust vectoring and plume charge neutralization, can be integrated into future designs with minimal additional cost. This project has matured the LTCC-ET development Technology Readiness Level (TRL) from 1 to 2. The low-cost RF plasma source portion of the LTCC device was matured from TRL 2 to 4 through the demonstration of RF plasma ignition under vacuum conditions.

Huang, P.-H. A.↗

CQNN: a CGRA-based QNN Framework

We propose a novel Coarse-Grained Reconfigurable Architecture-based (CGRA) QNN acceleration framework, CQNN. CQNN has a large number of basic components for binary functions. By programming CQNN at runtime according to the target QNN models, these basic components are integrated efficiently to support QNN functions with any data-width and hyper-parameter requirements and CQNN is reconfigured to have the optimal architecture for the target models. The framework includes compiler, architecture design, simulator and RTL generator. Experimental results show CQNNs can complete the inference of AlexNet and VGG-16 within 0.13ms and 2.63ms.

Geng, Tong↗

Delay-resolved spectroscopy in terahertz photonic circuits

Photonic integrated circuits incorporating intersubband transitions are ideal for mid-infrared and terahertz nanophotonics. However, the design of epitaxies has long been inhibited by two factors: the modest predictivity of ab initio theory and the absence of absolute intersubband gain and loss measurements under operating conditions. Existing measurements either yield inaccurate gain profiles or do not accurately assess dependence on frequency, bias, and temperature. Here, we present a delay-resolved absolute-referencing method for accurate gain evaluation without these limitations, addressing a long-standing challenge. By creating a photonic circuit that allows broadband pulses to traverse different lengths of a gain medium, we measure the absolute transmission of intersubband structures. Gain profiles match theoretical predictions at lower temperatures, with gain and dispersion clamping after lasing, and faster-than-expected degradation occurs at higher temperatures. Our approach provides a precise experimental evaluation of temperature-dependent gain performance and gives insight into optimizing temperature performance and frequency comb designs.

Optical spectroscopy↗

Techno-Economic Analysis of Gas-Liquid Contactors for Tritium Extraction from Lead-Lithium

To enable a sustainable fuel cycle, any deuterium-tritium fusion reactor must breed its tritium fuel onsite. Lead-lithium (PbLi), a eutectic metal, is a leading liquid breeder material for tritium generation. One challenge with PbLi blanket technology is the extraction of tritium from the molten eutectic. Three technologies are the focus of worldwide research: the vacuum permeator, the vacuum sieve tray, and the gas-liquid contactor (GLC). The present work offers a methodology for designing, sizing, optimizing, and costing a trickle-bed GLC. Here, we analyzed tritium extraction from PbLi using MELODIE experimental data by applying traditional packed bed mass transfer efficiency models along with supplementary models, like film theory. Our analysis revealed that traditional packed bed mass transfer efficiency models do not fit the MELODIE loop experimental data. Moreover, uncertainty in PbLi solubility resulted in a 325-fold increase in required gas flow rates when comparing identical packing heights. The film theory liquid mass transfer coefficient, Delt-Olujic wettability model, and Reiter tritium solubility values fit the MELODIE data best and were used both in the design and to conduct the economic analysis. Techno-economic analysis of the GLC was performed to evaluate three design sizes, all achieving a minimum extraction efficiency of 90 [%] for a total tritium extraction of 31 [kg/yr].

Fusion Fuel Cycle↗

Optimization of Thin Film Ferroelectrics for Communication Applications

The application of thin film ferroelectrics for the development of tunable microwave components have been a very active field of investigation thraughout the last decade. This presentation will provide an overview of some of the activities in the aforementioned area by other research groups and the current status of the field. In particular, we will discuss the efforts currently underway at the NASA Glenn Research Center in the area of phase shifter development using Ba2Sr(1-x)TiO3 ferroelectric thin films. Emphasis will be given to the approaches that have been investigated in order to improve the performance (i.e., figure of merit) of these devices. Some of these approaches deal with the details of circuit design parameters, while others are related to Experimental results and discussions on the aforementioned topics will be presented the optimization of material properties through different deposition techniques.

Miranda, Felix A.↗

Optimal Decision Making in High-Throughput Virtual Screening Pipelines

ABSTRACT Effective selection of the potential candidates that meet certain conditions in a tremendously large search space has been one of the major concerns in many real-world applications. In addition to the nearly infinitely large search space, rigorous evaluation of a sample based on the reliable experimental or computational platform is often prohibitively expensive, making the screening problem more challenging. In such a case, constructing a high-throughput screening (HTS) pipeline that pre-sifts the samples expected to be potential candidates through the efficient earlier stages, results in a significant amount of savings in resources. However, to the best of our knowledge, despite many successful applications, no one has studied optimal pipeline design or optimal pipeline operations. In this study, we propose two optimization frameworks, applying to most (if not all) screening campaigns involving experimental or/and computational evaluations, for optimally determining the screening thresholds of an HTS pipeline. We validate the proposed frameworks on both analytic and practical scenarios. In particular, we consider the optimal computational campaign for the long non-coding RNA (lncRNA) classification as a practical example. To accomplish this, we built the high-throughput virtual screening (HTVS) pipeline for classifying the lncRNA. The simulation results demonstrate that the proposed frameworks significantly reduce the effective selection cost per potential candidate and make the HTS pipelines less sensitive to their structural variations. In addition to the validation, we provide insights on constructing a better HTS pipeline based on the simulation results.

97 MATHEMATICS AND COMPUTING↗

Corrosion Testing Of Additively Manufactured Stainless Steel 316H In Molten Salt Environments

The development of a new ASTM standard for evaluating the corrosion resistance of additive manufactured (AM) stainless steel (SS) 316H in chloride molten salts is critical for the use of these materials in extreme environments such as molten salt reactors (MSRs). This report pertains to a work package of the Advaned Materials and Manufacturing Technologies (AMMT) developing a systematic methodology to link changes in AM fabrication parameters, namely surface finishing, porosity, microstructure, and chemical heterogeneity, to corrosion performance in NaCl-MgCl2 salt, a proposed secondary coolant for MSRs. During Fiscal Year 2024, Idaho National Laboratory investigators in the AMMT program, utilized SS316H bars, fabricated with laser bed powder fusion at Los Alamos National Laboratory, to establish and optimize the workflow for evaluating these process-to-performance relationships. Standard practices for specimen preparation were established using these specimens, with particular focus on descaling and sectioning methods that align with ASTM guidelines. A comprehensive experimental design for static corrosion testing was developed, with pre- and post-exposure analysis utilizing optical microscopy and scanning electron microscopy. So far standard descaling techniques were optimized, one static corrosion test was conducted on the LANL AM SS316H specimens, and pre- and post-corrosion practices were established. In addition, the work package yielded a review paper on corrosion testing gaps for AM materials in nuclear applications and submitted a proposal for a rapid-turnaround experiment to the Nuclear Science User Facilities Program to investigate the combined effects of proton irradiation and corrosion on AM SS316H. This work package establishes a foundation for evaluating processing-to-performance relationships for AM SS316H in harsh conditions, contributing to the safe and efficient design of components for next-generation nuclear reactors. The creation of a standardized methodology and the generation of relevant publications and future research pathways represent significant strides towards integrating AM materials into critical applications where corrosion resistance is paramount.

36 MATERIALS SCIENCE↗

FAIR Data and Interpretable AI Framework for Architectured Metamaterials

Our interdisciplinary effort successfully generated FAIR (Findable, Accessible, Interoperable, and Reusable) benchmark datasets for mechanical metamaterials while introducing a novel Artificial Intelligence (AI) framework known as Learning Refined Compositional Rules (LRCR). This framework was specifically designed to bridge the gap across varying computational length scales and extract the underlying physical mechanisms that connect a material's structural geometry to its bulk acoustic properties. Historically, the discovery of such structured materials relied heavily on human intuition or opaque, black-box optimization algorithms that were difficult to generalize. By combining interpretable machine learning techniques with rigorous experimental validation, this project established clear, generalizable design guidelines for tuning wave dispersion and controlling vibrations. Ultimately, the public availability of these structured datasets and algorithms will significantly reduce computational costs and accelerate the design of advanced multi-functional acoustic devices, offering broad societal impacts across fields like aerospace engineering, telecommunications, and biomedical implant design.

36 MATERIALS SCIENCE↗

Application of Taguchi methods to dual mixture ratio propulsion system optimization for SSTO vehicles

The application of advanced technologies to future launch vehicle designs would allow the introduction of a rocket-powered, single-stage-to-orbit (SSTO) launch system early in the next century. For a selected SSTO concept, a dual mixture ratio, staged combustion cycle engine that employs a number of innovative technologies was selected as the baseline propulsion system. A series of parametric trade studies are presented to optimize both a dual mixture ratio engine and a single mixture ratio engine of similar design and technology level. The effect of varying lift-off thrust-to-weight ratio, engine mode transition Mach number, mixture ratios, area ratios, and chamber pressure values on overall vehicle weight is examined. The sensitivity of the advanced SSTO vehicle to variations in each of these parameters is presented, taking into account the interaction of each of the parameters with each other. This parametric optimization and sensitivity study employs a Taguchi design method. The Taguchi method is an efficient approach for determining near-optimum design parameters using orthogonal matrices from design of experiments (DOE) theory. Using orthogonal matrices significantly reduces the number of experimental configurations to be studied. The effectiveness and limitations of the Taguchi method for propulsion/vehicle optimization studies as compared to traditional single-variable parametric trade studies is also discussed.

Stanley, Douglas O.↗

Achieving designed texture and flows in bulk active nematics using optimal control theory

Being intrinsically nonequilibrium, active materials can potentially perform functions that would be thermodynamically forbidden in passive materials. However, active systems have diverse local attractors that correspond to distinct dynamical states, many of which exhibit chaotic turbulent-like dynamics and thus cannot perform work or useful functions. Designing such a system to choose a specific dynamical state is a formidable challenge. Motivated by recent advances enabling optogenetic control of experimental active materials, we describe an optimal control theory framework that identifies a spatiotemporal sequence of light-generated activity that drives an active nematic system toward a prescribed dynamical steady state. Active nematics are unstable to spontaneous defect proliferation and chaotic streaming dynamics in the absence of control. We demonstrate that optimal control theory can compute activity fields that redirect the dynamics into a variety of alternative dynamical programs and functions. This includes dynamically reconfiguring between states, selecting and stabilizing emergent behaviors that do not correspond to attractors, and are hence unstable in the uncontrolled system. Furthermore, our results provide a roadmap to leverage optical control methods to rationally design structure, dynamics, and function in a wide variety of active materials.

Complex systems theory↗

Controls of interaction dynamics of orbital assembly

Building structures and spacecraft in orbit will require technologies for positioning, docking/berthing, and joining orbital structures. A fundamental problem underlying the operation of docking and berthing is that of controlling the contact dynamics of mechanical structures actuated by active mechanisms such as robotic devices. Control systems must be designed to control these active mechanisms so that both the free space motions and contact motions are stable and satisfy specifications on position accuracy and bounds on contact forces. For the large orbital structures of the future, the problem of interactive dynamics and control is fundamentally different in several ways than it was for spacecraft docking in the past. First, future space structures must be treated as flexible structures - the operations of docking, berthing, and assembly will need to respect the vibrations of the structures. Second, the assembly of these structures will require multiple-point contact, rather than the essentially single-point positioning of conventional spacecraft docking. Third, some assembly operations require the subassemblies to be brought and held in contact so that successful joining can be accomplished. A preliminary study of contact stability and compliance control design has resulted in the development of an analytical method and a design method to analyze stability. The analytical method analyzes the problem of stability when an actively-controlled structure contacts a passive structure. This method makes it possible to accurately estimate the stiffness of the passive structures with which the contact motion will become unstable. The analytic results suggest that passivity is neither achievable in practice, nor necessary as a design concept. A contact control system need only be passive up to a certain frequency; beyond that frequency the system can be stabilized with sufficiently small gains. With this concept the Center developed a design methodology for achieving desired compliant contact motions. This design method is based on H-infinity norm optimization, which makes it possible to consider both driving point mechanical impedance and systems robustness to modeling uncertainty. A laboratory facility was set up to verify experimentally the analytical and design theory.

Su, Renjeng↗

Application of direct inverse analogy method (DIVA) and viscous design optimization techniques

A direct-inverse approach to the transonic design problem was presented in its initial state at the First International Conference on Inverse Design Concepts and Optimization in Engineering Sciences (ICIDES-1). Further applications of the direct inverse analogy (DIVA) method to the design of airfoils and incremental wing improvements and experimental verification are reported. First results of a new viscous design code also from the residual correction type with semi-inverse boundary layer coupling are compared with DIVA which may enhance the accuracy of trailing edge design for highly loaded airfoils. Finally, the capabilities of an optimization routine coupled with the two viscous full potential solvers are investigated in comparison to the inverse method.

Greff, E.↗

Analysis of Photothermal Characterization of Layered Materials: Design of Optimal Experiments

In this paper numerical calculations are presented for the steady-periodic temperature in layered materials and functionally-graded materials to simulate photothermal methods for the measurement of thermal properties. No laboratory experiments were performed. The temperature is found from a new Green s function formulation which is particularly well-suited to machine calculation. The simulation method is verified by comparison with literature data for a layered material. The method is applied to a class of two-component functionally-graded materials and results for temperature and sensitivity coefficients are presented. An optimality criterion, based on the sensitivity coefficients, is used for choosing what experimental conditions will be needed for photothermal measurements to determine the spatial distribution of thermal properties. This method for optimal experiment design is completely general and may be applied to any photothermal technique and to any functionally-graded material.

Cole, Kevin D.↗

Investigating Liquid CO2 as a Coolant for a MTSA Heat Exchanger Design

Metabolic heat regenerated Temperature Swing Adsorption (MTSA) technology is being developed for thermal and carbon dioxide (CO 2) control for a future Portable Life Support System (PLSS), as well as water recycling. CO 2 removal and rejection is accomplished by driving a sorbent through a temperature swing of approximately 210 K to 280 K . The sorbent is cooled to these sub-freezing temperatures by a Sublimating Heat Exchanger (SHX) with liquid coolant expanded to sublimation temperatures. Water is the baseline coolant available on the moon, and if used, provides a competitive solution to the current baseline PLSS schematic. Liquid CO2 (LCO2) is another non-cryogenic coolant readily available from Martian resources which can be produced and stored using relatively low power and minimal infrastructure. LCO 2 expands from high pressure liquid (~5800 kPa) to Mars ambient (0.8 kPa) to produce a gas / solid mixture at temperatures as low as 156 K. Analysis and experimental work are presented to investigate factors that drive the design of a heat exchanger to effectively use this sink. Emphasis is given to enabling efficient use of the CO 2 cooling potential and mitigation of heat exchanger clogging due to solid formation. Minimizing mass and size as well as coolant delivery are also considered. The analysis and experimental work is specifically performed in an MTSA-like application to enable higher fidelity modeling for future optimization of a SHX design. In doing so, the work also demonstrates principles and concepts so that the design can be further optimized later in integrated applications (including Lunar application where water might be a choice of coolant).

Paul, Heather L.↗

Artificial Intelligence and Machine Learning for Bioenergy Research: Opportunities and Challenges

The integration of artificial intelligence and machine learning (AI/ML) with automated experimentation, genomics, biosystems design, and bioprocessing technologies is poised to revolutionize scientific investigation and, particularly, bioenergy research. To identify the opportunities and challenges in this emerging research area, the U.S. Department of Energy’s (DOE) Biological and Environmental Research program (BER) and Bioenergy Technologies Office (BETO) held a joint virtual workshop on AI/ML for Bioenergy Research (AMBER) on August 23–25, 2022. These interests have since been amplified in a September 2022 Executive Order, “Advancing Biotechnology and Biomanufacturing Innovation for a Sustainable, Safe, and Secure U.S. Bioeconomy,” to promote a whole-of government approach to biotechnology development (White House 2022). Approximately 50 scientists with various backgrounds and expertise from academia, industry, and DOE national laboratories met to discuss the opportunities and challenges of AI/ML for bioenergy research. Workshop participants were tasked with assessing the potential for AI/ML and laboratory automation to advance biological understanding and engineering in general. They particularly examined how integrating AI/ML tools with laboratory automation could accelerate biosystems design and optimize biomanufacturing. Discussions included the data and computational infrastructure needed to augment biosystems design applications and the expertise and workforce development efforts urgently required to shift integrated systems toward bioenergy research more broadly. Participants discussed many existing and future applications of AI/ML for biosystems design ranging from enzymes to plants and microbes, microbiomes, and bioprocess development. They also identified three key categories of scientific and technical opportunities and challenges: high-quality data, AI/ML algorithms, and laboratory automation. Several main takeaways emerged from the workshop: 1. Numerous AI/ML and automated experimentation applications exist for a variety of DOE mission needs in energy and the environment; 2. Exemplary research grand challenges for which AI/ML could provide solutions include: building microbes and microbial communities to specifications, developing closed-loop autonomous design and control for biosystems design, and advancing scale-up and automation; 3. Lack of sufficient high-quality, annotated data hinders the development of AI/ML applications; 4. New and improved AI/ML tools are needed, particularly those meeting the specific needs of the BER and BETO research communities; 5. Trade-offs in performance, cost, and reliability exist between deploying commercially available versus building custom-developed instrumentation and software for automated or autonomous experimentation; translation of manual to automated or autonomous methods is often a nontrivial endeavor; 6. Training a new generation of young scientists who can develop and apply AI/ML tools is needed to solve long-standing scientific challenges in bioenergy research. The integration of AI/ML tools and automated experimentation represents a new data-driven research paradigm complementary to the traditional hypothesis-driven research paradigm. This paradigm accelerates design and optimization of biological systems and processes for a variety of DOE mission needs in energy and the environment. The AMBER workshop broadly explored the potential of this new paradigm for bioenergy research, of particular interest to BER and BETO, and identified key challenges and opportunities that DOE can address in the coming years by leveraging its unique capabilities and resources.

59 BASIC BIOLOGICAL SCIENCES↗