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All sources NASA NTRS DOE OSTI

DOE OSTI2022

Network Uncertainty Quantification for Analysis of Multi-Component Systems

To impact physical mechanical system design decisions and realize the full promise of high-fidelity computational tools, simulation results must be integrated at the earliest stages of the design process. This is particularly challenging when dealing with uncertainty and optimizing for system-level performance metrics, as full-system models (often notoriously expensive and time-consuming to develop) are generally required to propagate uncertainties to system-level quantities of interest. Methods for propagating parameter and boundary condition uncertainty in networks of interconnected components hold promise for enabling design under uncertainty in real-world applications. These methods avoid the need for time consuming mesh generation of full-system geometries when changes are made to components or subassemblies. Additionally, they explicitly tie full-system model predictions to component/subassembly validation data which is valuable for qualification. These methods work by leveraging the fact that many engineered systems are inherently modular, being comprised of a hierarchy of components and subassemblies that are individually modified or replaced to define new system designs. By doing so, these methods enable rapid model development and the incorporation of uncertainty quantification earlier in the design process. The resulting formulation of the uncertainty propagation problem is iterative. We express the system model as a network of interconnected component models, which exchange solution information at component boundaries. We present a pair of approaches for propagating uncertainty in this type of decomposed system and provide implementations in the form of an open-source software library. We demonstrate these tools on a variety of applications and demonstrate the impact of problem-specific details on the performance and accuracy of the resulting UQ analysis. This work represents the most comprehensive investigation of these network uncertainty propagation methods to date.

42 ENGINEERING↗

DOE OSTI2018

Feedstock powder processing research needs for additive manufacturing development

Additive manufacturing (AM) promises to redesign traditional manufacturing by enabling the ultimate in agility for rapid component design changes in commercial products and for fabricating complex integrated parts. Here, by significantly increasing quality and yield of metallic alloy powders, the pace for design, development, and deployment of the most promising AM approaches can be greatly accelerated, resulting in rapid commercialization of these advanced manufacturing methods. By successful completion of a critical suite of processing research tasks that are intended to greatly enhance gas atomized powder quality and the precision and efficiency of powder production, researchers can help promote continued rapid growth of AM. Finally, other powder-based or spray-based advanced manufacturing methods could also benefit from these research outcomes, promoting the next wave of sustainable manufacturing technologies for conventional and advanced materials.

36 MATERIALS SCIENCE↗

NASA NTRS1990

Synthesis: Intertwining product and process

Synthesis is a proposed systematic process for rapidly creating different members of a program family. Family members are described by variations in their requirements. Requirements variations are mapped to variations on a standard design to generate production quality code and documentation. The approach is made feasible by using principles underlying design for change. Synthesis incorporates ideas from rapid prototyping, application generators, and domain analysis. The goals of Synthesis and the Synthesis process are discussed. The technology needed and the feasibility of the approach are also briefly discussed. The status of current efforts to implement Synthesis methodologies is presented.

Weiss, David M.↗

DOE OSTI2026

wa-hls4ml: A Benchmark and Surrogate Models for hls4ml Resource and Latency Estimation

As machine learning (ML) is increasingly implemented in hardware to address real-time challenges in scientific applications, the development of advanced toolchains has significantly reduced the time required to iterate on various designs. These advancements have solved major obstacles, but also exposed new challenges. For example, processes that were not previously considered bottlenecks, such as hardware synthesis, are becoming limiting factors in the rapid iteration of designs. To mitigate these emerging constraints, multiple efforts have been undertaken to develop an ML-based surrogate model that estimates resource usage of ML accelerator architectures. We introduce wa-hls4ml, a benchmark for ML accelerator resource and latency estimation, and its corresponding initial dataset of over 680,000 fully connected and convolutional neural networks, all synthesized using hls4ml and targeting Xilinx FPGAs. The benchmark evaluates the performance of resource and latency predictors against several common ML model architectures, primarily originating from scientific domains, as exemplar models, and the average performance across a subset of the dataset. Additionally, we introduce GNN- and transformer-based surrogate models that predict latency and resources for ML accelerators. We present the architecture and performance of the models and find that the models generally predict latency and resources for the 75% percentile within several percent of the synthesized resources on the synthetic test dataset.

Hawks, Benjamin [Fermilab] (ORCID:0000000157000288↗

DOE OSTI2024

Reaction engineering: a lost (and found) art for a decarbonized future [Slides]

The heart (or, perhaps more appropriately, the stomach) of any chemical manufacturing process is the reactor, where chemical and physical transformations occur under precisely controlled conditions. For traditional industrial processes, the design, optimization and operation of chemical reactors are extremely well developed, drawing upon the principles of chemistry, physics, calculus and economics. However, new-age process concepts proposing to use "exotic" reactors and/or sustainable inputs (e.g., renewable carbon resources, electrons, photons, plasma) face a dearth of well documented reaction engineering principles & design practices that eclipses their rapid adoption. This presentation features two vignettes of (the return of) reaction engineering in sustainable process science, first in the valorization of lignin from biomass, and second in understanding multimodal catalyst deactivation in industrial-scale reactors within the Catofin process for propane dehydrogenation. Overall, this seminar seeks to educate student researchers on practical means of advancing laboratory reactor technologies towards commercial practice.

09 BIOMASS FUELS↗

DOE OSTI2025

wa-hls4ml: A Benchmark and Surrogate Models for hls4ml Resource and Latency Estimation

As machine learning (ML) is increasingly implemented in hardware to address real-time challenges in scientific applications, the development of advanced toolchains has significantly reduced the time required to iterate on various designs. These advancements have solved major obstacles, but also exposed new challenges. For example, processes that were not previously considered bottlenecks, such as hardware synthesis, are becoming limiting factors in the rapid iteration of designs. To mitigate these emerging constraints, multipleefforts have been undertaken to develop an ML-based surrogate model that estimates resource usage of synthesized ML accelerator architectures. We introduce wa-hls4ml, a benchmark for ML accelerator resource and latency estimation, and its corresponding initial dataset of over 680 000 fully connected and convolutional neural networks, all synthesized using hls4ml and targeting Xilinx FPGAs. The benchmark evaluates the performance of resource and latency predictors against several common ML model architectures, primarily originating from scientific domains, as exemplar models, and the average performance across a subset of the dataset. Additionally, we introduce GNN- and transformer-based surrogate models that predict latency and resources for ML accelerators. We present the architecture and performance of the models and find that the models generally predict latency and resources for the 75% percentile within several percent of the synthesized resources on the synthetic test dataset.

Hawks, Benjamin G. [Fermilab]↗

DOE OSTI2023

A customized MOF-polymer composite for rapid gold extraction from water matrices

With the fast-growing accumulation of electronic waste and rising demand for rare metals, it is compelling to develop technologies that can promotionally recover targeted metals, like gold, from waste, a process referred to as urban mining. Thus, there is increasing interest in the design of materials to achieve rapid, selective gold capture while maintaining high adsorption capacity, especially in complex aqueous-based matrices. Here, a highly porous metal-organic framework (MOF)–polymer composite, BUT-33–poly(para-phenylenediamine) (PpPD), is assessed for gold extraction from several matrices including river water, seawater, and leaching solutions from CPUs. BUT-33–PpPD exhibits a record-breaking extraction rate, with high Au3+ removal efficiency (>99%) within seconds (less than 45 s), a competitive capacity (1600 mg/g), high selectivity, long-term stability, and recycling ability. Furthermore, the high porosity and redox adsorption mechanism were shown to be underlying reasons for the material’s excellent performance. Given the accumulation of recovered metallic gold nanoparticles inside, the material was also efficiently applied as a catalyst.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS2004

IpexT: Integrated Planning and Execution for Military Satellite Tele-Communications

The next generation of military communications satellites may be designed as a fast packet-switched constellation of spacecraft able to withstand substantial bandwidth capacity fluctuation in the face of dynamic resource utilization and rapid environmental changes including jamming of communication frequencies and unstable weather phenomena. We are in the process of designing an integrated scheduling and execution tool which will aid in the analysis of the design parameters needed for building such a distributed system for nominal and battlefield communications. This paper discusses the design of such a system based on a temporal constraint posting planner/scheduler and a smart executive which can cope with a dynamic environment to make a more optimal utilization of bandwidth than the current circuit switched based approach.

Plaunt, Christian↗

DOE OSTI2022

Rapid assessment of interfacial stabilization mechanisms of metastable precipitates to accelerate high-temperature Al-alloy development

Precipitate strengthened high-temperature alloys are currently used in safety-critical applications. Understanding precipitate stability and solute segregation mechanisms at high temperatures is key to designing high-strength alloys. Rapid in-situ approaches, therefore, are pivotal in accelerating the alloy design process. Hereby using the test case of a promising high-temperature Al-Cu-Mn-Zr alloy, we demonstrate the value of in-situ atom probe tomography coupled with in-situ transmission electron microscopy to reveal atomic-scale mechanisms that lead to the emergence of non-equilibrium solute segregation. Mn and Zr segregation at strengthening precipitate(θ’)-matrix interface increases the kinetic barrier for phase transformation thus retaining high-temperature strength.

36 MATERIALS SCIENCE↗

DOE OSTI2013

First-order convex feasibility algorithms for x-ray CT

Purpose: Iterative image reconstruction (IIR) algorithms in computed tomography (CT) are based on algorithms for solving a particular optimization problem. Design of the IIR algorithm, therefore, is aided by knowledge of the solution to the optimization problem on which it is based. Often times, however, it is impractical to achieve accurate solution to the optimization of interest, which complicates design of IIR algorithms. This issue is particularly acute for CT with a limited angular-range scan, which leads to poorly conditioned system matrices and difficult to solve optimization problems. In this paper, we develop IIR algorithms which solve a certain type of optimization called convex feasibility. The convex feasibility approach can provide alternatives to unconstrained optimization approaches and at the same time allow for rapidly convergent algorithms for their solution-thereby facilitating the IIR algorithm design process. Methods: An accelerated version of the Chambolle-Pock (CP) algorithm is adapted to various convex feasibility problems of potential interest to IIR in CT. One of the proposed problems is seen to be equivalent to least-squares minimization, and two other problems provide alternatives to penalized, least-squares minimization. Results: The accelerated CP algorithms are demonstrated on a simulation of circular fan-beam CT with a limited scanning arc of 144 Degree-Sign . The CP algorithms are seen in the empirical results to converge to the solution of their respective convex feasibility problems. Conclusions: Formulation of convex feasibility problems can provide a useful alternative to unconstrained optimization when designing IIR algorithms for CT. The approach is amenable to recent methods for accelerating first-order algorithms which may be particularly useful for CT with limited angular-range scanning. The present paper demonstrates the methodology, and future work will illustrate its utility in actual CT application.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2014

Modern steels at atomic and nanometre scales

Processing bulk nanocrystalline materials for structural applications still poses a difficult challenge, particularly in achieving an industrially viable process. Recent work in ferritic steels has proved that it is possible to move from ultrafine to nanoscale by exploiting the bainite reaction without the use of severe deformation, rapid heat treatment or mechanical processing. This new generation of steels has been designed in which transformation at low temperature leads to a nanoscale structure consisting of extremely fine, 20–40 nm thick plates of bainitic ferrite and films of retained austenite. Finally, a description of the characteristics and significance of this remarkable microstructure is provided here.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2017

Structural Evaluation of Complex Subcomponents Manufactured by Large Scale Extrusion Deposition of Carbon Fiber Reinforced ABS

The large scale extrusion deposition process has recently been commercialized in the form of additive manufacturing machines such as the BAAM from Cincinnati Inc., which enables layered production of chopped fiber reinforced thermoplastic polymer systems. The application of this process to the automotive market is being pursued by Local Motors to enable rapid design to market cycles and build on-demand capability for a wide range of vehicle styles from a distributed network of micro-factories. This endeavor will require an understanding of the structural performance of components with complex geometries, where the properties are known to vary as a function of printing conditions, as well as orientation and shape. In order to rapidly build a database of structural performance, a beam specimen with outer dimensions of 914 x 305 x 64 mm3 was selected to be subjected to bending, torsion, and shear loading with full field displacement measurement by digital image correlation (DIC). A total of 25 different specimen configurations were designed including variation of print geometry, reinforcement by foam filling, and overwrapping with advanced composites. This work documents the results of the study and presents the relative performance of the structures in addition to the approach to simulation that is being initiated to serve as a framework for efficient design of structures manufactured in this way. The results are presented as a table of structural efficiency including stiffness and strength as functions of mass for each design. Additional results will also be provided in the form of surface displacements from DIC; future work will utilize this data to better optimize simulations for predicting structural performance of articles manufactured by this process.

Bedsole, Robert↗

NASA NTRS1981

Design, evaluation, and fabrication of low-cost composite blades for intermediate-size wind turbines

Low cost approaches for production of 60 ft long glass fiber/resin composite rotor blades for the MOD-OA wind turbine were identified and evaluated. The most cost-effective configuration was selected for detailed design. Subelement and subscale specimens were fabricated for testing to confirm physical and mechanical properties of the composite blade materials, to develop and evaluate blade fabrication techniques and processes, and to confirm the structural adequacy of the root end joint. Full-scale blade tooling was constructed and a partial blade for tool and process tryout was built. Then two full scale blades were fabricated and delivered to NASA-LeRC for installation on a MOD-OA wind turbine at Clayton, New Mexico for operational testing. Each blade was 60 ft. long with 4.5 ft. chord at root end and 2575 lbs weight including metal hub adapter. The selected blade configuration was a three cell design constructed using a resin impregnated glass fiber tape winding process that allows rapid wrapping of primarily axially oriented fibers onto a tapered mandrel, with tapered wall thickness. The ring winder/transverse filament tape process combination was used for the first time on this program to produce entire rotor blade structures. This approach permitted the complete blade to be wound on stationary mandrels, an improvement which alleviated some of the tooling and process problems encountered on previous composite blade programs.

Weingart, O.↗

NASA NTRS2002

Flexible Wing Base Micro Aerial Vehicles: Composite Materials for Micro Air Vehicles

This paper will discuss the development of the University of Florida's Micro Air Vehicle concept. A series of flexible wing based aircraft that possess highly desirable flight characteristics were developed. Since computational methods to accurately model flight at the low Reynolds numbers associated with this scale are still under development, our effort has relied heavily on trial and error. Hence a time efficient method was developed to rapidly produce prototype designs. The airframe and wings are fabricated using a unique process that incorporates carbon fiber composite construction. Prototypes can be fabricated in around five man-hours, allowing many design revisions to be tested in a short period of time. The resulting aircraft are far more durable, yet lighter, than their conventional counterparts. This process allows for thorough testing of each design in order to determine what changes were required on the next prototype. The use of carbon fiber allows for wing flexibility without sacrificing durability. The construction methods developed for this project were the enabling technology that allowed us to implement our designs. The resulting aircraft were the winning entries in the International Micro Air Vehicle Competition for the past two years. Details of the construction method are provided in this paper along with a background on our flexible wing concept.

Ifju, Peter G.↗

DOE OSTI2025

wa-hls4ml and lui-gnn: A benchmark and GNN-based surrogate model for hls4ml resource and latency estimation

As machine learning (ML) increasingly serves as a tool for addressing real-time challenges in scientific applications, the development of advanced tooling has significantly reduced the time required to iterate on various designs. These advancements have solved major obstacles, but also exposed new challenges. For example, processes that were not previously considered bottlenecks, such as model synthesis, are now becoming limiting factors in the rapid iteration of designs. To reduce these emerging constraints, multiple efforts are being launched toward designing an ML-based surrogate model that estimates resource usage of synthesized accelerator architectures. This model would reduce the design iteration time, especially when designing within a set of given hardware constraints. This approach shows considerable potential, but as it stands, the effort is early and would benefit from coordination and standardization to assist future work as it emerges. We introduce wa-hls4ml, a benchmark for ML accelerator resource and latency estimation, and its corresponding initial dataset of more than 100,000 fully connected neural networks, all synthesized using hls4ml and targeting Xilinx FPGAs. In addition to the resource utilization and latency data provided, the dataset includes generated artifacts and log files for many of the synthesized neural networks, in order to support future research in ML-based code generation. The benchmark evaluates the performance of resource and latency predictors against several common ML model architectures, primarily originating from scientific domains, as exemplar models, as well as the average performance across a subset of the dataset. We measure the performance of a given predictor model through multiple metrics, including $R^2$ score and SMAPE on regression tasks, as well as inference time to further characterize the estimator under test. Additionally, we introduce the latency/utilization inference graph neural network (lui-gnn), a surrogate model that uses a graph neural network to represent input architectures in the form of a directed graph. This graph representation allows for a diverse set of model architectures to all be effectively handled by a surrogate model. We present the architecture and performance of the model, as evaluated by the new proposed benchmark, including SMAPE, $R^2$ score, and inference times, and find that lui-gnn generally predicts latency and utilization for the 75\% quantile within several percent of the synthesized resources on the synthetic test dataset, indicating that this approach of estimating resource and latency via a surrogate models has promise and warrants further research.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2021

RapidClave® Technology Demonstrations – II Hat Stiffener

This project sought to evaluate the cost and performance of both polymeric and metallic tooling for use with the RapidClave® composite process. Teijin’s rapid cure carbon/epoxy prepreg, Q183, was selected to fabricate demonstration components, of aerospace design, which currently are fabricated via compression molding using matched steel tooling. The ability to fabricate components using this prepreg in the RapidClave®, and using low cost single sided tooling, could significantly reduce the cost of part manufacture and shorten production lead times for tooling fabrication. The component demonstration article was a “hat stiffener” geometry typically used to reinforce fuselage or wing skins of an aircraft. A rapid preforming process was demonstrated and rapid process cycle times similar to compression molding were achieved by placing the preform on hot tooling, thus avoiding the time and energy associated with typical thermal cycling. A 90% reduction in tooling cost was achieved through the use of single sided aluminum or polymeric additive tooling when compared to compression molding matched steel tooling. In addition to rapid cycle times, RapidClave® offers the ability to change out tooling in minutes such that multiple part geometries can be fabricated in one shift.

36 MATERIALS SCIENCE↗

NASA NTRS2013

Centrifugal Sieve for Gravity-Level-Independent Size Segregation of Granular Materials

Conventional size segregation or screening in batch mode, using stacked vibrated screens, is often a time-consuming process. Utilization of centrifugal force instead of gravity as the primary body force can significantly shorten the time to segregate feedstock into a set of different-sized fractions. Likewise, under reduced gravity or microgravity, a centrifugal sieve system would function as well as it does terrestrially. When vibratory and mechanical blade sieving screens designed for terrestrial conditions were tested under lunar gravity conditions, they did not function well. The centrifugal sieving design of this technology overcomes the issues that prevented sieves designed for terrestrial conditions from functioning under reduced gravity. These sieves feature a rotating outer (cylindrical or conical) screen wall, rotating fast enough for the centrifugal forces near the wall to hold granular material against the rotating screen. Conventional centrifugal sieves have a stationary screen and rapidly rotating blades that shear the granular solid near the stationary screen, and effect the sieving process assisted by the airflow inside the unit. The centrifugal sieves of this new design may (or may not) have an inner blade or blades, moving relative to the rotating wall screen. Some continuous flow embodiments would have no inner auger or blades, but achieve axial motion through vibration. In all cases, the shearing action is gentler than conventional centrifugal sieves, which have very high velocity differences between the stationary outer screen and the rapidly rotating blades. The new design does not depend on airflow in the sieving unit, so it will function just as well in vacuum as in air. One advantage of the innovation for batch sieving is that a batch-mode centrifugal sieve may accomplish the same sieving operation in much less time than a conventional stacked set of vibrated screens (which utilize gravity as the primary driving force for size separation). In continuous mode, the centrifugal sieves can provide steady streams of fine and coarse material separated from a mixed feedstock flow stream. The centrifugal sieves can be scaled to any desired size and/or mass flow rate. Thus, they could be made in sizes suitable for small robotic exploratory missions, or for semi-permanent processing of regolith for extraction of volatiles of minerals. An advantage of the continuous-mode system is that it can be made with absolutely no gravity flow components for feeding material into, or for extracting the separated size streams from, the centrifugal sieve. Thus, the system is capable of functioning in a true microgravity environment. Another advantage of the continuous-mode system is that some embodiments of the innovation have no internal blades or vanes, and thus, can be designed to handle a very wide range of feedstock sizes, including occasional very large oversized pieces, without jamming or seizing up.

Walton, Otis R.↗

NASA NTRS2003

Rapid Prototyping of an Aircraft Model in an Object-Oriented Simulation

A team was created to participate in the Mars Scout Opportunity. Trade studies determined that an aircraft provided the best opportunity to complete the science objectives of the team. A high fidelity six degree of freedom flight simulation was required to provide credible evidence that the aircraft design fulfilled mission objectives and to support the aircraft design process by providing performance evaluations. The team created the simulation using the Langley Standard Real-Time Simulation in C++ (LaSRS++) application framework. A rapid prototyping approach was necessary because the team had only three months to both develop the aircraft simulation model and evaluate aircraft performance as the design and mission parameters matured. The design of LaSRS++ enabled rapid-prototyping in several ways. First, the framework allowed component models to be designed, implemented, unit-tested, and integrated quickly. Next, the framework provides a highly reusable infrastructure that allowed developers to maximize code reuse while concentrating on aircraft and mission specific features. Finally, the framework reduces risk by providing reusable components that allow developers to build a quality product with a compressed testing cycle that relies heavily on unit testing of new components.

Kenney, P. Sean↗