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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 37 records · Page 2

Nanotechnology: From Science Fiction to Reality

Nanotechnology promises unconventional solutions to challenging problems because of expectations that matter can be manipulated at the atomic scale to yield properties that exceed those predicted for bulk materials. The excitement at this possibility has been fueled by significant investments in this technology area. This talk will focus on three examples of where advances are being made to exploit unique properties made possible by nanoscale features for aerospace applications. The first two topics will involve the development of carbon nanotubes for (a) lightweight structural applications and (b) net shape fabricated multifunctional components. The third topic will highlight lessons learned from the demonstration of the effect of nanoengineered surfaces on insect residue adhesion. In all three cases, the approaches used to mature these emerging technologies are based on the acceleration of technology development through multidisciplinary collaborations.

Siochi, Mia↗

Flutter Prediction for Aircraft Conceptual Design

Flutter prediction is usually a knowledge-based analysis process that aims to reduce the cost of aeroelastic stability margin certification. However, early detection of flutter problems is beneficial in the development of unconventional aircraft. The recently developed automation tool ConceptFEA for structural sizing of aircraft concepts paves the way for rapid physics-based flutter prediction of aircraft concepts. A match-point iteration procedure using the p-k method is implemented for ConceptFEA with minimum user input requirements to generate flutter boundary points. A subsonic business jet concept and its high aspect-ratio wing variant are used to demonstrate how the newly developed flutter prediction capability can be used during aircraft conceptual design. Sized structures, flutter boundary curves, and flutter sensitivity analysis results are generated for these two concepts using ConceptFEA. The relevant equivalent plate theory is provided to show the quantitative relationships between a stiffened panel and its equivalent NASTRAN PSHELL panel. The rapid flutter prediction capability of ConceptFEA makes multidisciplinary collaborations between systems analysts and aeroelasticity experts feasible in practice.

Li, Wu↗

Experiences in the Practice of Design of Experiments at NASA

Statistical design of experiments (DOE) has gained recognition within NASA by spurring innovation and efficiency, and it has demonstrated significant impact. Aerospace research and development benefits DOE techniques by accelerating learning, maximizing knowledge, ensuring strategic resource investment, and informing data-driven decisions. In practice, DOE relies on multidisciplinary collaboration to develop solution strategies that integrate statistical methods with subject-matter expertise to meet challenging research objectives. This presentation shares experiences in the practice of design of experiments at NASA in aeronautics, space exploration, and atmospheric science.

Peter A. Parker↗

Statistical Practice and Research at NASA

The discipline of statistics has gained recognition within NASA by spurring innovation and efficiency, and it has demonstrated significant impact and value. In aerospace research and development, it accelerates learning, maximizes knowledge, ensures strategic resource investment, and informs rigorous data-driven decisions. In practice, it requires immersive multidisciplinary collaboration to develop solution strategies that integrate statistical methods with subject-matter expertise to address challenging research objectives. This presentation provides an overview of statistical case studies in aeronautics, space exploration, and atmospheric science, and it highlights statistical research motivated by NASA’s challenging applications.

Peter A. Parker↗

Towards Lightweight Data Integration Using Multi-Workflow Provenance and Data Observability

Modern large-scale scientific discovery requires multidisciplinary collaboration across diverse computing facilities, including High Performance Computing (HPC) machines and the Edge-to-Cloud continuum. Integrated data analysis plays a crucial role in scientific discovery, especially in the current AI era, by enabling Responsible AI development, FAIR, Reproducibility, and User Steering. However, the heterogeneous nature of science poses challenges such as dealing with multiple supporting tools, cross-facility environments, and efficient HPC execution. Building on data observability, adapter system design, and provenance, we propose MIDA: an approach for lightweight runtime Multi-workflow Integrated Data Analysis. MIDA defines data observability strategies and adaptability methods for various parallel systems and machine learning tools. With observability, it intercepts the dataflows in the background without requiring instrumentation while integrating domain, provenance, and telemetry data at runtime into a unified database ready for user steering queries. We conduct experiments showing end-to-end multi-workflow analysis integrating data from Dask and MLFlow in a real distributed deep learning use case for materials science that runs on multiple environments with up to 276 GPUs in parallel. We show near-zero overhead running up to 100,000 tasks on 1,680 CPU cores on the Summit supercomputer.

Santos Souza, Renan↗

The Industry's Long-term, Yet Near-term, Issues: The Need for Radiation Protection Professionals - 20266

Since the discovery of X-rays and radioactivity, the civil use of nuclear technology has thrived for more than a half-century and has matured to be safer and more efficient. A balance between radiological and non-radiological knowledge and experience has been gained and retained through the years. Nevertheless, a slowly developing gap has emerged during the past few decades. National and international data show a declining trend in the existence of health physics programs and associated enrollment and training, which directly impact the pipeline of radiation professionals (i.e., educators, technicians, researchers, and regulators). This decline can be attributed to many factors including the lack of scientific inquisitiveness, declining funding, and the perception that existing protocols are sufficiently protective. Decommissioning and dismantling nuclear facilities is a complex and multi-phased process that generates large quantities of various levels of radioactive waste. With multiple facilities reaching their end of operational life, and others being shut down for economic reasons, the current pipeline for radiation protection experts cannot meet the future's need. Consequently, international organizations have proposed a variety of programs to transfer knowledge of radiation protection principles and practice. While many change-oriented efforts to counteract this trend aim to promote mobility, this is just a partial solution to the actual issue: long-term availability. This paper suggests multidisciplinary collaborations with modern technologies as a path forward to educate young professionals on the diversity of radiation-related applications to retain expert knowledge and foster innovation. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Data Communications Requirements for CAS Applications

This paper discusses the long-haul data communications requirements needed to support visualization of Computational Aeroscience (CAS) simulations. A scientific computing model is presented, from which current communications requirements are derived. This model is then expanded to describe the CAS Collaborative Visualization Environment, in which scientists from multiple NASA centers will collaborate on multidisciplinary, time-accurate simulations. An analysis of this model, along with data from the TFCC Workload Model, shows that CAS data communications requirements will increase to 10-100 megabytes/second by 1996.

McCabe, James D.↗

Brookhaven Lab Hosts Hackathon Focused on Graphics Processing Units (GPUs)

For five days in June 2017, Brookhaven Lab’s Computational Science Initiative hosted “Brookathon”—a programming workshop where teams of researchers, students, and software developers worked with mentors to accelerate scientific applications on GPUs for high-performance computing.

97 MATHEMATICS AND COMPUTING↗

Qualitative Study of Interprofessional Collaboration in Radiation Oncology Clinics: Is There a Need for Further Education?

Interprofessional education (IPE) is gaining recognition as a means of improving health care delivery and patient outcomes. A primary goal of IPE is improved interprofessional collaboration (IPC). The multidisciplinary team in the radiation oncology clinic requires effective IPC for optimal delivery of radiation therapy. However, there are limited data on IPE and IPC in radiation oncology. This qualitative study aims to characterize IPC in radiation oncology.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Multi-Scale Modeling and Prototype Development for Electrochemical CO2 Reduction (CRADA Final Report)

In this CRADA project, Lawrence Livermore National Laboratory, Stanford University, SLAC National Laboratory, and TotalEnergies collaboratively executed a multidisciplinary investigation of electrochemical reduction of CO2 to produce sustainable fuels and chemicals. Overall, the project led to an increased understanding of the fundamental processes involved in CO2 electrolysis, from the atomistic scale to the full electrolyzer device scale, ultimately leading to design guidelines for CO2 electrolyzers that will help in their future commercialization. As the model systems, Ag- and Cu-based catalysts were investigated in various forms depending on the electrochemical platform that was utilized to study the activity, selectivity, and durability towards electrochemical CO2 reduction. By employing experimental, theoretical, and computational techniques, the project team experimentally validated multi-physics models, evaluated the experimental levers that lead to increased electrolyzer reaction selectivity and energy efficiency, and used computational optimization to design higher performance electrodes. The learnings of this project were extensively documented in publicly available peer-reviewed journal publications and conference presentations, which serve as a foundation for further work to build from.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Algorithms and Object-Oriented Software for Distributed Physics-Based Modeling

The project seeks to develop methods to more efficiently simulate aerospace vehicles. The goals are to reduce model development time, increase accuracy (e.g.,by allowing the integration of multidisciplinary models), facilitate collaboration by geographically- distributed groups of engineers, support uncertainty analysis and optimization, reduce hardware costs, and increase execution speeds. These problems are the subject of considerable contemporary research (e.g., Biedron et al. 1999; Heath and Dick, 2000).

Kenton, Marc A.↗

Multidisciplinary design optimization in Architecture, Engineering, and Construction: a detailed review and call for collaboration

The design of buildings has become a complex and multidisciplinary problem involving multiple conflicting objectives as architects and designers address competing technical, economic, environmental, and societal concerns. This has been driving research in Architecture, Engineering, and Construction (AEC) toward rigorous multidisciplinary decision-making frameworks that generate and evaluate numerous design alternatives using multi-objective optimization in concert with simulation and analysis models of varying fidelity and computational expense. While such frameworks are well known and widely employed in the aerospace and systems engineering domains, efforts by design professionals and researchers in the AEC field are scattered at best. In this paper, we provide a detailed review of recent developments in optimization frameworks in the AEC field and subsequently highlight how such developments are largely compartmentalized into separate domains such as structural, energy, daylighting, and other performance factors. Herein, we further discuss the technical challenges involved in concurrent coupled multidisciplinary design optimization (MDO) in the AEC field such as interoperability issues between Building Information Modeling (BIM) environments, analysis/simulation tools, and optimization frameworks. We conclude by outlining research needed for more unified modeling and simulation-based optimization frameworks to aid in complex and multidisciplinary building design processes. We also highlight the need for the identification and development of multi-fidelity simulation tools for use across multiple design phases. As such, this paper contributes a novel roadmap to leverage aerospace and systems engineering research in MDO into the field of AEC, along with a call for researchers in the MDO community to seek collaborations in AEC field.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Implementation and Performance Issues in Collaborative Optimization

Collaborative optimization is a multidisciplinary design architecture that is well-suited to large-scale multidisciplinary optimization problems. This paper compares this approach with other architectures, examines the details of the formulation, and some aspects of its performance. A particular version of the architecture is proposed to better accommodate the occurrence of multiple feasible regions. The use of system level inequality constraints is shown to increase the convergence rate. A series of simple test problems, demonstrated to challenge related optimization architectures, is successfully solved with collaborative optimization.

Braun, Robert↗

Introduction

The 2014 SPIE Sensing Technologies for Global Health, Military Medicine and Environmental Monitoring conference embraced a wealth of state-of-the-art information in basic and applied science. This event covered the latest developments in the following areas: Non-invasive Disease Diagnostics for Global Health- This opening series of two consecutive sessions focused on oral biospecimen based rapid assays and point-of-care devices for the detection of pathogens causing infectious diseases, biomarkers for cancer, and analytes for noncommunicable diseases such as diabetes. They also covered presentations on the human proteasome and microbiome with linkage to human diseases and diagnostic approaches. The sessions were built on the past experience and expertise of the National Institutes of Health, National Institutes of Dental and Craniofacial Research. Military Medicine I: Traumatic Brain Injury and PTSD-This assembly covered oral-biomarker based diagnostics for brain damage and TBI as well as prevention and rehabilitation technologies. Neurorehabilitation and noninvasive neuromodulation were also discussed as critical approaches for effective functioning. Military Medicine II: Physiology and Medicine of Extreme Environments and Spaceflight-This scientific segment showcased physiological, pharmacological and diagnostic sensing methodologies during spaceflight per the National Aeronautics and Space Administration as well as military-relevant toxicans and future sensing trends per the Department of Defense. It also included latest technologies to determine hydration status in warfighters, eye surgery using the latest laser technologies, and sensing tools for blood analysis.  Sensing Technologies for Disease Diagnostics and Environmental Monitoring-This closing series of two consecutive sessions provided the venues to learn and discuss more results on the next generation of diagnostic tools and field technologies for diseases, including biomarker detection by digital imaging, multiplex technologies, capillary electrophoresis and molecular platforms serving as labs-on-chips. This conference allowed cross-fertilization of ideas, projects and collaborative work by a multidisciplinary audience of national and international colleagues from the academia, industry and federal government: The National Institutes of Health, National Aeronautics and Space Administration, and the Department of Defense.

Wotring, Virginia E.↗

Use of the Collaborative Optimization Architecture for Launch Vehicle Design

Collaborative optimization is a new design architecture specifically created for large-scale distributed-analysis applications. In this approach, problem is decomposed into a user-defined number of subspace optimization problems that are driven towards interdisciplinary compatibility and the appropriate solution by a system-level coordination process. This decentralized design strategy allows domain-specific issues to be accommodated by disciplinary analysts, while requiring interdisciplinary decisions to be reached by consensus. The present investigation focuses on application of the collaborative optimization architecture to the multidisciplinary design of a single-stage-to-orbit launch vehicle. Vehicle design, trajectory, and cost issues are directly modeled. Posed to suit the collaborative architecture, the design problem is characterized by 5 design variables and 16 constraints. Numerous collaborative solutions are obtained. Comparison of these solutions demonstrates the influence which an priori ascent-abort criterion has on development cost. Similarly, objective-function selection is discussed, demonstrating the difference between minimum weight and minimum cost concepts. The operational advantages of the collaborative optimization

Braun, R. D.↗

Advanced Information Technology in Simulation Based Life Cycle Design

In this research a Collaborative Optimization (CO) approach for multidisciplinary systems design is used to develop a decision based design framework for non-deterministic optimization. To date CO strategies have been developed for use in application to deterministic systems design problems. In this research the decision based design (DBD) framework proposed by Hazelrigg is modified for use in a collaborative optimization framework. The Hazelrigg framework as originally proposed provides a single level optimization strategy that combines engineering decisions with business decisions in a single level optimization. By transforming this framework for use in collaborative optimization one can decompose the business and engineering decision making processes. In the new multilevel framework of Decision Based Collaborative Optimization (DBCO) the business decisions are made at the system level. These business decisions result in a set of engineering performance targets that disciplinary engineering design teams seek to satisfy as part of subspace optimizations. The Decision Based Collaborative Optimization framework more accurately models the existing relationship between business and engineering in multidisciplinary systems design.

Renaud, John E.↗

Collaborative Experiments and Computations in Aircraft Icing

The formation of ice over lifting surfaces can affect aerodynamic performance. The ability to predict ice accumulation and the resulting degradation in vehicle performance is essential to determine the limitations of aircraft in icing encounters. The consequences of underestimating performance degradation can be serious and so it is important to produce accurate predictions, particularly for severe icing conditions. The simulation of ice accretion is a challenging multidisciplinary problem that requires close collaboration between the computational and ground test communities. This paper describes three recent case studies and the lessons learned through collaborative experiments and computations in aircraft icing- one for large commercial transports, one for rotorcraft, and one dealing with icing on regional jets.

and rotorcraft↗

NEAMS Workbench Workflows

Modeling and simulation efforts frequently involve loosely coupled workflows. Automation of workflows, data exchanges, and simulation software execution is a productive and often desired feature or improvement for enhancing consistency of results and productivity of the analyst. It facilitates cross-collaboration of different analysts of multidisciplinary simulation by streamlining data exchange processes across local and high performance computing resources. This report proposes a high-level, extensible workflow module to enable consistent and efficient use of tools integrated into the Nuclear Energy Advanced Modeling and Simulation (NEAMS) Workbench with as little user intervention as possible.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗