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NASA NTRS2006

The Zero-Degree Detector System for Fragmentation Studies

The measurement of nuclear fragmentation cross sections requires the detection and identification of individual projectile fragments. If light and heavy fragments are recorded in 'ne same detector, it may be impossible distinguish the signal from the light fragment. To overcome this problem, we have developed the Zero-Degree Detector System. The ZDDS enables the measurement of cross sections for light fragment production by using pixelated detectors to separately measure the signals of each fragment. The system has been used to measure the fragmentation of beams as heavy as Fe at the NASA Space Radiation Laboratory at Brookhaven National Laboratory and the Heavy Ion Medical Accelerator in Chiba, Japan.

Adams, J. H., Jr.↗

DOE OSTI2024

Personalized, disease-stage specific, rapid identification of immunosuppression in sepsis

Introduction Data overlapping of different biological conditions prevents personalized medical decision-making. For example, when the neutrophil percentages of surviving septic patients overlap with those of non-survivors, no individualized assessment is possible. To ameliorate this problem, an immunological method was explored in the context of sepsis. Methods Blood leukocyte counts and relative percentages as well as the serum concentration of several proteins were investigated with 4072 longitudinal samples collected from 331 hospitalized patients classified as septic (n=286), non-septic (n=43), or not assigned (n=2). Two methodological approaches were evaluated: (i) a reductionist alternative, which analyzed variables in isolation; and (ii) a non-reductionist version, which examined interactions among six (leukocyte-, bacterial-, temporal-, personalized-, population-, and outcome-related) dimensions. Results The reductionist approach did not distinguish outcomes: the leukocyte and serum protein data of survivors and non-survivors overlapped. In contrast, the non-reductionist alternative differentiated several data groups, of which at least one was only composed of survivors (a finding observable since hospitalization day 1). Hence, the non-reductionist approach promoted personalized medical practices: every patient classified within a subset associated with 100% survival subset was likely to survive. The non-reductionist method also revealed five inflammatory or disease-related stages (provisionally named ‘early inflammation, early immunocompetence, intermediary immuno-suppression, late immuno-suppression, or other’). Mortality data validated these labels: both ‘suppression’ subsets revealed 100% mortality, the ‘immunocompetence’ group exhibited 100% survival, while the remaining sets reported two-digit mortality percentages. While the ‘intermediary’ suppression expressed an impaired monocyte-related function, the ‘late’ suppression displayed renal-related dysfunctions, as indicated by high concentrations of urea and creatinine. Discussion The data-driven differentiation of five data groups may foster early and non-overlapping biomedical decision-making, both upon admission and throughout their hospitalization. This approach could evaluate therapies, at personalized level, earlier. To ascertain repeatability and investigate the dynamics of the ‘other’ group, additional studies are recommended.

Immunology↗

NASA NTRS1973

Program of policy studies in science and technology

The application of an interdisciplinary, problem-oriented capability to the performance of total social impact evaluations is discussed. The consequences of introducing new configurations, technological or otherwise into future social environments are presented. The primary characteristics of the program are summarized: (1) emphasis on interdisciplinary, problem-oriented analysis; (2) development of intra- and inter-institutional arrangements for the purpose of analyzing social problems, evaluating existing programs, and assessing the social impacts of prospective policies, programs, and other public actions; (3) focus on methodological approaches to the projection of alternative future social environments, the identification of the effects of the introduction of new policies, programs, or other actions into the social system, and the evaluation of the social impacts of such effects; (4) availability of analytical resources for advisory and research tasks, and provision for use of program facilities as a neutral forum for the discussion of public issues involving involving the impact of advancing technology on social value-institutional processes.

Mayo, L. H.↗

NASA NTRS1978

Numerical method for solution of systems of non-stationary spatially one-dimensional nonlinear differential equations

A computational scheme and a standard program is proposed for solving systems of nonstationary spatially one-dimensional nonlinear differential equations using Newton's method. The proposed scheme is universal in its applicability and its reduces to a minimum the work of programming. The program is written in the FORTRAN language and can be used without change on electronic computers of type YeS and BESM-6. The standard program described permits the identification of nonstationary (or stationary) solutions to systems of spatially one-dimensional nonlinear (or linear) partial differential equations. The proposed method may be used to solve a series of geophysical problems which take chemical reactions, diffusion, and heat conductivity into account, to evaluate nonstationary thermal fields in two-dimensional structures when in one of the geometrical directions it can take a small number of discrete levels, and to solve problems in nonstationary gas dynamics.

Morozov, S. K.↗

NASA NTRS1991

High energy from space

The following subject areas are covered: (1) important scientific problems for high energy astrophysics (stellar activity, the interstellar medium in galaxies, supernovae and endpoints of stellar evolution, nucleosynthesis, relativistic plasmas and matter under extreme conditions, nature of gamma-bursts, identification of black holes, active nuclei, accretion physics, large-scale structures, intracluster medium, nature of dark matter, and the X- and gamma-ray background); (2) the existing experimental programs (Advanced X-Ray Astrophysics Facility (AXAF), Gamma Ray Observatory (GRO), X-Ray Timing Explorer (XTE), High Energy Transient Experiment (HETE), U.S. participation in foreign missions, and attached Shuttle and Space Station Freedom payloads); (3) major missions for the 1990's; (4) a new program of moderate missions; (5) new opportunities for small missions; (6) technology development issues; and (7) policy issues.

Margon, Bruce↗

NASA NTRS1993

A layered approach to structural control system design for the JPL phase B testbed

This paper describes our efforts in structural control experiments for a flexible precision structure using both passive and active control. Specifically, a layered structural control approach utilizing passive viscous dampers, colocated and noncolocated active control is used. The passive dampers and active colocated control loops are used to enhance stability and robustness and the noncolocated multivariable controller is designed with respect to a partially controlled structure to further improve the performance. Our approach to the multivariable design problem requires not only a state space model description of the plant, but also an accompanying uncertainty model. To support the multivariable robust control design development, a significant effort in system identification was undertaken. The process of identification and identified results are discussed. Noncolocated controllers are designed using the H(infinity)/mu-synthesis methodology. The order of the controller is typically large, hence, model reduction is performed for practical digital implementation on a real-time control system developed at JPL. Finally, experimental results are presented and some of lessons are discussed.

Chu, Cheng-Chih↗

NASA NTRS2006

Developing Formal Correctness Properties from Natural Language Requirements

This viewgraph presentation reviews the rationale of the program to transform natural language specifications into formal notation.Specifically, automate generation of Linear Temporal Logic (LTL)correctness properties from natural language temporal specifications. There are several reasons for this approach (1) Model-based techniques becoming more widely accepted, (2) Analytical verification techniques (e.g., model checking, theorem proving) significantly more effective at detecting types of specification design errors (e.g., race conditions, deadlock) than manual inspection, (3) Many requirements still written in natural language, which results in a high learning curve for specification languages, associated tools and increased schedule and budget pressure on projects reduce training opportunities for engineers, and (4) Formulation of correctness properties for system models can be a difficult problem. This has relevance to NASA in that it would simplify development of formal correctness properties, lead to more widespread use of model-based specification, design techniques, assist in earlier identification of defects and reduce residual defect content for space mission software systems. The presentation also discusses: potential applications, accomplishments and/or technological transfer potential and the next steps.

requirements engineering↗

NASA NTRS2006

Educational Experiences of Embry-Riddle Students through NASA Research Collaboration

NASA's educational. programs benefit students and faculty while increasing the overall productivity of the organization. The NASA Graduate Student Research Program (GSRP) awards fellowships for graduate study leading to both masters and doctoral degrees in several technical fields. GSRP participants have the option to utilize NASA Centers andlor university research facilities. In addition, GSRP students can serve as mentors for undergrad students to provide a truly unique learning experience. NASA's Cooperative Education Program allows undergraduate students the chance to gain "real-world" work experience in the field. It also gives NASA a no risk capability to evaluate the true performance of a prospective new hire without relying solely on a "paper resume" while providing the students with a greater hiring potential upon graduation, at NASA or elsewhere. University faculty can also benefit by participating in the NASA Faculty Fellowship Program (NFFP). This program gives the faculty an opportunity to work with NASA peers. The Mission Analysis Branch of the Expendable Launch Vehicles Division at NASA Kennedy Space Center has utilized these two programs with students from Embry-Riddle Aeronautical University (ERAU) to conduct research in modeling and developing a parameter estimation method for spacecraft fuel slosh using simple pendulum analogs. Simple pendulum models are used to understand complicated spacecraft fuel slosh behavior. A robust parameter estimation process will help to identif' the parameters that will predict the response fairly accurately during the initial stages of design. These programs provide students with a unique opportunity to work on "real-world" aerospace problems, like spacecraft fuel slosh,. This in turn reinforces their problem solving abilities and their communication skills such as interviewing, resume writing, technical writing, and presentation. Faculty benefits by applying what they have learned to the classroom. Through university collaborations with NASA and industry help students to acquire skills that are vital for their success upon entering the workforce.

Schlee, Keith↗

NASA NTRS2020

Application of Sparse Identification of Nonlinear Dynamics for Physics-Informed Learning

Advances in machine learning and deep neural networks has enabled complex engineering tasks like image recognition, anomaly detection, regression, and multi-objective optimization, to name but a few. The complexity of the algorithm architecture, e.g., the number of hidden layers in a deep neural network, typically grows with the complexity of the problems they are required to solve, leaving little room for interpreting (or explaining) the path that results in a specific solution. This drawback is particularly relevant for autonomous aerospace and aviation systems, where certifications require a complete understanding of the algorithm behavior in all possible scenarios. Including physics knowledge in such data-driven tools may improve the interpretability of the algorithms, thus enhancing model validation against events with low probability but relevant for system certification. Such events include, for example, spacecraft or aircraft sub-system failures, for which data may not be available in the training phase. This paper investigates a recent physics-informed learning algorithm for identification of system dynamics, and shows how the governing equations of a system can be extracted from data using sparse regression. The learned relationships can be utilized as a surrogate model which, unlike typical data-driven surrogate models, relies on the learned underlying dynamics of the system rather than large number of fitting parameters. The work shows that the algorithm can reconstruct the differential equations underlying the observed dynamics using a single trajectory when no uncertainty is involved. However, the training set size must increase when dealing with stochastic systems, e.g., nonlinear dynamics with random initial conditions.

Corbetta, Matteo↗

DOE OSTI2022

Investigations on a fuzzy process: effect of diffusion on calibration and particle identification in Liquid Argon Time Projection Chambers

Ionization electron diffusion in Liquid Argon Time Projection Chambers (LArTPCs) has typically been considered at the detector design stage, but little attention has been given to its effects on calibration and particle identification. We use a GEANT4-based simulation to study how diffusion impacts these techniques, and give consideration to how this effect is simulated. We find that diffusion can cause a drift-dependent bias to both the median and Most Probable Value (MPV) of dQ/dx distributions. The bias is estimated to be ~2.5% (median) and ~5.0% (MPV) for typical maximum drift times in currently running LArTPCs before adding detector specific considerations such as electric field non-uniformities. This information indicates that these metrics should not be used for calibration without care, contrary to the conventional wisdom. The impact of diffusion on the ability of LArTPCs to separate muons and protons is small, and not expected to pose any problems in future detectors. Diffusion may however be a significant source of systematic uncertainty when separating particles of more similar masses (muons and pions, kaons and protons). Separation of such populations may be improved by implementation of a drift-time dependent particle identification.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2021

JTAG-based PLC memory acquisition framework for industrial control systems

In industrial control systems (ICS), programmable logic controllers (PLC) are the embedded devices that directly control and monitor critical industrial infrastructure processes such as nuclear plants and power grid stations. Cyberattacks often target PLCs to sabotage a physical process. A memory forensic analysis of a suspect PLC can answer questions about an attack, including compromised firmware and manipulation of PLC control logic code and I/O devices. Given physical access to a PLC, collecting forensic information from the PLC memory at the hardware-level is risky and challenging. It may cause the PLC to crash or hang since PLCs have proprietary, legacy hardware with heterogeneous architecture. This paper addresses this research problem and proposes a novel JTAG (Joint Test Action Group)-based framework, Kyros, for reliable PLC memory acquisition. Kyros systematically creates a JTAG profile of a PLC through hardware assessment, JTAG pins identification, memory map creation, and optimizing acquisition parameters. It also facilitates the community of interest (such as ICS owners, operators, and vendors) to develop the JTAG profiles of PLCs. Further, we present a case study of Kyros implementation over Allen-Bradley 1756-A10/B to help understand the framework's application on a real-world PLC used in industry settings. The sample PLC memory dumps are shared with the research community to facilitate further research.

Rais, Muhammad Haris↗

NASA NTRS1993

Cosmic physics data analysis program

A data analysis program was carried out to investigate the intensity, propagation, and origin of primary Cosmic Ray Galactic electrons. Scanning was carried out on two new balloon flight experiments as well as the border area of previous experiments. The identification and evaluation of the energies of the primary electrons were carried out. A new analysis of these data were incorporated into an overall evaluation of the roll of electrons in the problem of the origin of cosmic rays. Recent measurements indicate that the earth may be within the expanding Geminga supernova shock wave which is expected to have a major effect upon the propagation and the energy spectrum of galactic electrons. Calculations with the Geminga model indicate that the cut-off energy may be very close to the observed highest energy electrons in our analysis.

Wilkes, R. Jeffrey↗

NASA NTRS2010

Risk as a Driver for Innovation

The Space Life Sciences directorate (SLSD) and Human Research Program (HRP) at NASA Johnson Space Center has implemented a system for managing human systems risks. These risks are defined as the health and performance risks posed to crew during and after spaceflight. Identification and evaluation of these risks has led to the identification of gaps in knowledge about the risks as well as gaps in technology needed to mitigate them. Traditional routes of closing technology gaps have, in some cases, proven to be too slow when a solution was required quickly. Therefore, certain gaps were used to drive the development of "challenges" for the scientific community. Partnering with open innovation service providers such as InnoCentive and Yet2.com, SLSD and HRP have decreased the amount of time from identification of a need to the evaluation of a solution. Although not all proposed solutions will result in a risk mitigation strategy or tool, the process has allowed faster evaluation of proposed solutions providing the researcher the ability to move to another possible solution if the first does not sufficiently address the problem. Moreover, this process engages the community outside of NASA and broadens the population from which to draw solutions. In the traditional grant funding structure, only those in the specific field will apply for the grant. However, using open innovation, solutions can come from individuals in many different fields. This can expand the general view of a field (way of thinking within a field) and the application of solutions form new fields while providing a pathway for the acquisition of novel solutions or refinements of current mitigations. Identification of the human systems risks has helped drive the development and evaluation of innovative solutions as well as engaging a broader scientific audience in working with NASA.

Davis, Jeff↗

NASA NTRS1989

The generalized drift flux approach: Identification of the void-drift closure law

The main characteristics and the potential advantages of generalized drift flux models are presented. In particular it is stressed that the issue on the propagation properties and on the mathematical nature (hyperbolic or not) of the model and the problem of closure are easier to tackle than in two fluid models. The problem of identifying the differential void-drift closure law inherent to generalized drift flux models is then addressed. Such a void-drift closure, based on wave properties, is proposed for bubbly flows. It involves a drift relaxation time which is of the order of 0.25 s. It is observed that, although wave properties provide essential closure validity tests, they do not represent an easily usable source of quantitative information on the closure laws.

Boure, J. A.↗

NASA NTRS1988

Optimal experiment design for on-orbit identification

An optimal on-orbit experiment is designed to extract the most information from an on-orbit test, subject to the constraints of the testing environment. However, simply jumping in and optimizing standard measures of information with respect to the experiment design can cause severe problems if attention is not paid to the specific needs and properties of the problem at hand. The actual criteria to be optimized depends on (among other things) the particular ID algorithm and parametrization being used. Two parametric techniques are the focus of this presentation: recursive prediction error method (RPEM) and maximum likelihood estimation (MLE).

Bayard, David S.↗

DOE OSTI2026

A large-scale benchmarking of deterministic and stochastic derivative-free optimization algorithms

This presentation summarizes our work in the PrOMMiS project on benchmarking of data-driven optimization algorithms and their applications in self-driving laboratories. This work supports the broader project goal of accelerating the identification of promising separation methods and operating conditions for critical minerals separation processes. We present a systematic benchmarking study of 42 data-driven optimization algorithms on a broad collection of 502 test problems. The results identify BAM, GLCCLUSTER, and MULTIMIN as the most effective optimization solvers, with BAM showing the highest overall performance and solving more than 80% of the benchmark problems. The study also shows that no single solver consistently outperforms the others across all problem types, indicating that our future laboratory applications may benefit from using a small set of strong solvers rather than relying on a single method. The presentation also illustrates an in-silico chemical reactor case study showing that data-driven optimization methods can guide autonomous experimentation in a self-driving laboratory and identify optimal operating conditions within a small number of experiments. Overall, the results provide a basis for selecting efficient optimization methods and demonstrate the practical use of data-driven optimization in self-driving laboratory workflows.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Algorithm-guided experimentation for autonomous AI systems in self-driving laboratories

36 MATERIALS SCIENCE↗

NASA NTRS1982

The effects of seasonal differences in climatic conditions on Landsat spectral signatures and associated land cover classification

Unsupervised classification algorithms are used to analyze Landsat computer-compatible tape data for an area of approximately 840 sq km in central Oklahoma, over the period from June 12 to August 4, 1979. The results obtained show that changes in remotely sensed spectral signatures and land cover classes are associated with a period of transition from moisture availability in late spring to moisture deficit in midsummer, with the latter being marked by greater visible spectrum reflectance and greater near-IR absorption, although each surface cover type has responded differently to the seasonal change in water availability. Consideration of these results has led to the identification of important factors in the use of multidate satellite data in environmental change monitoring. Naturally induced trends in surface albedo introduce noise into studies aimed at identifying anthropogenic land cover change. Specific problems associated with prairie-forest ecotonal areas in the southern Great Plains involve the seasonally induced differences in separability of forest, bush, and grassland cover types.

Harrington, J. A., Jr.↗