Search NASA⌕ Search

SEARCH · Search NASA

Results for “Design Information Verification”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

Recommendation for a Medical System Concept of Operations for Gateway Missions

NASA’s exploration missions to cis-lunar space will establish a permanent gateway to future transport missions to Mars. These missions mandate a significant paradigm change for mission planning, spacecraft design, human systems integration, and in-flight medical care due to constraints on mass, volume, power, resupply, and medical evacuation capability. These constraints require medical system development to be tightly integrated with mission and habitat design to provide a sufficient medical infrastructure and enable mission success. This concept of operations provides a vision of medical care needs that will be used to guide the development of a medical system for the cis-lunar Gateway Habitat. This medical system will serve as the precursor to what is implemented in future exploration missions to Mars. This concept of operations documents an overview of the stakeholder needs and system goals of a medical system and provides examples of the types of activities for which the system will be used during the mission. This concept of operations informs the ExMC systems engineering effort to define the Gateway Habitat Medical System by documenting the medical activities and capabilities relevant to Gateway missions, as identified by the ExMC clinician community. In addition, this concept of operations will inform the subsequent systems engineering process of developing technical requirements, system architectures, interfaces, and verification and validation approaches for the medical system. This document supports the closure of ExMC Gap Med01: We do not have a concept of operations for medical care during exploration missions, corresponding to the ExMC-managed human system risk: Risk of Adverse Health Outcomes & Decrements in Performance due to Inflight Medical Conditions.

Rubin, David↗
NASA NTRS1997

Automation Bias and Countermeasures in Flight Crews

Results of recent research investigating the use of automated systems have indicated the presence of automation bias, a term describing errors made when decision makers rely on automated cues as a heuristic replacement for vigilant information seeking and processing. Automation commission errors, i.e., errors made when decision makers take inappropriate action because they over-attend to automated information or directives, and automation omission errors, i.e., errors made when decision makers do not take appropriate action because they are not informed of an imminent problem or situation by automated aids, can result from this tendency. In a series of studies, participants who perceived themselves as "accountable" for their strategies of interaction with automation were significantly more likely to verify its correct functioning, and committed significantly fewer automation-related errors than those who did not report this perception. In this study, we focus on two manipulations to encourage verification behaviors within cockpit crews. The first, an information/training manipulation, will focus on explicit information on automation bias, and training for verification of automated functioning. The second manipulation will consist of display prompts to verify automated functioning. Participants (glass-cockpit crews) will fly a series of approaches on the Mini-ACFS, a two-person pan-task flight simulator. Approach scenarios include several automation "events," that is, glitches, malfunctions, or inappropriate recommendations, that can be caught if cross-checked with other cockpit indicators. We anticipate that these manipulations will ameliorate automation bias. Final data analysis will be completed prior to the OSU symposium, and is expected to support the hypotheses that: a) reduced errors are associated with verification behaviors; b) crews will be more likely to verify under training/display conditions than when in the control condition; and c) effects will persist when subjects return for a follow-up exercise 6-9 weeks after their first session. Implications for training and automation design will be discussed.

Mosier, Kathleen, L.↗
NASA NTRS2010

Decision Engines for Software Analysis Using Satisfiability Modulo Theories Solvers

The area of software analysis, testing and verification is now undergoing a revolution thanks to the use of automated and scalable support for logical methods. A well-recognized premise is that at the core of software analysis engines is invariably a component using logical formulas for describing states and transformations between system states. The process of using this information for discovering and checking program properties (including such important properties as safety and security) amounts to automatic theorem proving. In particular, theorem provers that directly support common software constructs offer a compelling basis. Such provers are commonly called satisfiability modulo theories (SMT) solvers. Z3 is a state-of-the-art SMT solver. It is developed at Microsoft Research. It can be used to check the satisfiability of logical formulas over one or more theories such as arithmetic, bit-vectors, lists, records and arrays. The talk describes some of the technology behind modern SMT solvers, including the solver Z3. Z3 is currently mainly targeted at solving problems that arise in software analysis and verification. It has been applied to various contexts, such as systems for dynamic symbolic simulation (Pex, SAGE, Vigilante), for program verification and extended static checking (Spec#/Boggie, VCC, HAVOC), for software model checking (Yogi, SLAM), model-based design (FORMULA), security protocol code (F7), program run-time analysis and invariant generation (VS3). We will describe how it integrates support for a variety of theories that arise naturally in the context of the applications. There are several new promising avenues and the talk will touch on some of these and the challenges related to SMT solvers. Proceedings

Bjorner, Nikolaj↗
NASA NTRS1989

Probabilistic design analysis using Composite Loads Spectra (CLS) coupled with Probabilistic Structural Analysis Methodologies (PSAM)

Composite loads spectra (CLS) were applied to generate probabilistic loads for use in the PSAM nonlinear evaluation of stochastic structures under stress (NESSUS) finite element code. The CLS approach allows for quantifying loads as mean values and distributions around a central value rather than maximum or enveloped values typically used in deterministic analysis. NESSUS uses these loads to determine mean and perturbation responses. These results are probabilistically evaluated with the distributional information from CLS using a fast probabilistic integration (FPI) technique to define response distributions. The main example discussed describes a method of obtaining load descriptions and stress response of the second-stage turbine blade of the Space Shuttle Main Engine (SSME) high-pressure fuel turbopump (HPFTP). Additional information is presented on the on-going analysis of the high pressure oxidizer turbopump discharge duct (HPOTP) where probabilistic dynamic loads have been generated and are in the process of being used for dynamic analysis. Example comparisons of load analysis and engine data are furnished for partial verification and/or justification for the methodology.

Newell, J. F.↗
DOE OSTI2024

The Release of the Simplified Radionuclide Transport (SRT) Code (V.2.1)

Reactor licensing centers on the protection of the public and environment from the inadvertent release of radioactive material. Therefore, mechanistic source term analysis, or the realistic evaluation of radionuclide transport from the source to the environment for specific transient scenarios, is vital to reactor licensing efforts. Developed to resolve a gap in mechanistic source term modeling capabilities for sodium fast reactors (SFRs), the Simplified Radionuclide Transport (SRT) code created by Argonne National Laboratory (Argonne) is now utilized by advanced reactor vendors, universities, and research institutions to support a multitude of design, licensing, and research efforts. Recently, SRT version 2.1 was released, which includes improvements to code models and verification and validation (V&V) suite to support the SRT user community. The following work provides an overview of the improvements made as part of the release of SRT version 2.1. This effort is supported by the U.S. Department of Energy Office of Nuclear Energy (DOE:NE) Advanced Reactor Technologies (ART) Fast Reactor Program (FRP), as part of the program’s support of national laboratory design and safety analysis computer codes utilized by the fast reactor industry. The expansion of SRT code capabilities and improvements to code V&V associated with version 2.1 are in response to user requests and lessons learned from recent source term analyses performed by Argonne and advanced reactor vendors. They also align with the evolving role of SRT, from research and development tool to software utilized for reactor licensing calculations. The report is structured in alignment with the code improvements, as outlined in Figure 1-1. Section 2 provides background information on SRT, including its history, capabilities, and utilization. Section 3 details new code capabilities as part of version 2.1, while Section 4 focuses on the expansion of the code’s V&V suite. Lastly, Section 5 provides a summary and discussion of next steps.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS2007

Human Factors in the Design of the Crew Exploration Vehicle (CEV)

NASA s Space Exploration vision for humans to venture to the moon and beyond provides interesting human factors opportunities and challenges. The Human Engineering group at NASA has been involved in the initial phases of development of the Crew Exploration Vehicle (CEV), Orion. Getting involved at the ground level, Human Factors engineers are beginning to influence design; this involvement is expected to continue throughout the development lifecycle. The information presented here describes what has been done to date, what is currently going on, and what is expected in the future. During Phase 1, prior to the contract award to Lockheed Martin, the Human Engineering group was involved in generating requirements, conducting preliminary task analyses based on interviews with subject matter experts in all vehicle systems areas, and developing preliminary concepts of operations based on the task analysis results. In addition, some early evaluations to look at CEV net habitable volume were also conducted. The program is currently in Phase 2, which is broken down into design cycles, including System Readiness Review, Preliminary Design Review, and Critical Design Review. Currently, there are ongoing Human Engineering Technical Interchange Meetings being held with both NASA and Lockheed Martin in order to establish processes, desired products, and schedules. Multiple design trades and quick-look evaluations (e.g. display device layout and external window size) are also in progress. Future Human Engineering activities include requirement verification assessments and crew/stakeholder evaluations of increasing fidelity. During actual flights of the CEV, the Human Engineering group is expected to be involved in in-situ testing and lessons learned reporting, in order to benefit human space flight beyond the initial CEV program.

Whitmore, Mihriban↗
DOE OSTI2021

Analysis of PNAR Spent Fuel Safeguards Measurements using the ORIGEN Data Analysis Module

This paper summarizes the analysis of the Passive Neutron Albedo Reactivity (PNAR) measurements using the ORIGEN data analysis module for 23 boiling water reactor spent fuel assemblies that were performed in Finland under an international collaboration on spent fuel safeguards verification methods. PNAR is part of the proposed integrated nondestructive system to be used for safeguards verifications at the planned Finnish encapsulation facility. Besides measuring passive neutron and gamma emission rates from an assembly like a Fork detector, PNAR also measures the PNAR ratio, which is expected to correlate with the fissile content in the assembly. The emission rates and PNAR ratio can be used to verify the operator declarations and the fissile content of an assembly, respectively. The analysis was performed using the ORIGEN Data Analysis Module, which was originally developed for predicting Fork detector neutron and gamma signals for spent fuel measurements and has been integrated into the Integrated Review and Analysis Package developed by Euratom and the IAEA. The Module includes the ORIGEN burnup analysis code and integrates detector response functions pre-generated using MCNP to predict detector signals in several seconds per assembly. In this study, new response functions specific to PNAR measurements were generated for ORIGEN Module. The study also analyzes impacts of using detailed fuel design and operation information vs. standard safeguards information on results calculated by ORIGEN Module. Using detailed information reduced the standard deviation of relative differences between calculated and measured neutron count rates among the 23 assemblies from ~10% to ~4%. The results obtained using standard safeguards information for these PNAR measurements were similar to those obtained for the Fork detector. A clear trend was found between the calculated net neutron multiplications and the measured PNAR ratios of the 23 assemblies. This paper describes how ORIGEN Module calculates the expected PNAR neutron and gamma signals and PNAR ratio and how they compare with corresponding measured values.

Ilas, Germina↗
DOE OSTI2020

An Energy Calculator for Simple Commercial Buildings

According to the EIA, simple commercial buildings account for 97% of total commercial building stock. However, most simple commercial buildings for example small- to mid-sized offices, retail, schools and warehouses do not benefit from the data-driven decision-making capabilities of whole-building energy modeling. The high cost of custom modeling limits the use of energy modeling of simple buildings for new construction or retrofit measures. Lack of tools providing helpful information on interactive savings estimates creates difficulties in meeting aggressive decarbonization and energy efficiency goals for simple building designers and utility program managers. This paper reviews a beta phase Simple Building Calculator with the ability to generate relatively accurate and interactive modeling results based on a limited but robust set of inputs. It can evaluate whole-building or single measure savings in new or existing buildings, compare measure package choices, or provide simplified performance modeling for energy codes and utility incentives. The tool combines physical (annual whole building prototype simulation) and statistical modeling techniques to predict annual energy performance. It supports a variety of building characteristics for envelope, HVAC, and lighting with parameters ranging from vintage to max tech configurations, as well as support for single-zone and simple multi-zone HVAC systems. The Simple Building Calculator was designed to provide immediate feedback for otherwise computationally intensive tasks like measure comparison, development of multiple measure package combinations, or verification that measures meet efficiency targets—all with the goal of providing a tool for quick annual energy simulation of simple commercial buildings.

Hart, Reid↗
DOE OSTI2020

Exploration of Domain Aware Machine Learning for Grid Analytics: Transfer-Learnt Energy Models to Assist Buildings Control with Sparse Field Data

Buildings are a primary consumer of energy in the United States and are also increasingly being perceived as providers of grid services such as load shifting, shedding and modulation. High fidelity models of building energy consumption are needed to set appropriate baselines for measurement and verification (M&V) of controllers designed for energy efficient operation of buildings and to enable buildings to provide grid services via. participation in demand response programs. State-of-the-art building energy modeling techniques either rely on Physics based models, or extensive instrumentation of the building envelope to gather “big” data to train machine learning based models such as deep neural networks. While Physics based models are often limited by their accuracy, it is not always feasible to gather a significant amount of field data required to train machine learning based models with sufficient accuracy. In this paper, we explore the use of transfer learning-based strategies to address unsatisfactory accuracy of models for estimating building energy consumption when available field data for training is sparse or of unacceptable quality. In particular, we transfer knowledge in the form of data and parameters, from Physics based simulation frameworks to the field to improve the model accuracy, thus resulting in a Physics-informed Machine Learning framework. We evaluated the efficacy of our approach on field data collected from six commercial buildings and our results indicate that the proposed transfer learning based models provide comparative (and in some cases better) accuracy than state-of-the-art machine learning and deep learning solutions, with just one month of field data.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2017

Risk-Significant Adverse Condition Awareness Strengthens Assurance of Fault Management Systems

As spaceflight systems increase in complexity, Fault Management (FM) systems are ranked high in risk-based assessment of software criticality, emphasizing the importance of establishing highly competent domain expertise to provide assurance. Adverse conditions (ACs) and specific vulnerabilities encountered by safety- and mission-critical software systems have been identified through efforts to reduce the risk posture of software-intensive NASA missions. Acknowledgement of potential off-nominal conditions and analysis to determine software system resiliency are important aspects of hazard analysis and FM. A key component of assuring FM is an assessment of how well software addresses susceptibility to failure through consideration of ACs. Focus on significant risk predicted through experienced analysis conducted at the NASA Independent Verification Validation (IVV) Program enables the scoping of effective assurance strategies with regard to overall asset protection of complex spaceflight as well as ground systems. Research efforts sponsored by NASA's Office of Safety and Mission Assurance defined terminology, categorized data fields, and designed a baseline repository that centralizes and compiles a comprehensive listing of ACs and correlated data relevant across many NASA missions. This prototype tool helps projects improve analysis by tracking ACs and allowing queries based on project, mission type, domaincomponent, causal fault, and other key characteristics. Vulnerability in off-nominal situations, architectural design weaknesses, and unexpected or undesirable system behaviors in reaction to faults are curtailed with the awareness of ACs and risk-significant scenarios modeled for analysts through this database. Integration within the Enterprise Architecture at NASA IVV enables interfacing with other tools and datasets, technical support, and accessibility across the Agency. This paper discusses the development of an improved workflow process utilizing this database for adaptive, risk-informed FM assurance that critical software systems will safely and securely protect against faults and respond to ACs in order to achieve successful missions.

Fault management↗
NASA NTRS1994

TOPEX/POSEIDON mission overview

TOPEX/POSEIDON is the first space mission specifically designed and conducted for studying the circulation of the world's oceans. A state-of-the-art radar altimetry system is used to measure the precise height of sea level, from which information on the ocean circulation is obtained. The satellite, launched on August 10, 1992, has been making observations of the global oceans with unprecedented accuracy since late September 1992. To meet the stringent measurement accuracy required for ocean circulation studies, a number of innovative improvements have been made to the mission design, including the first dual-frequency space-borne radar altimeter capable of retrieving the ionospheric delay of the radar signal, a three-frequency microwave radiometer for retrieving the signal delay caused by the water vapor in the troposphere, an optimal model of the Earth's gravity field and multiple satellite tracking systems for precision orbit determination. Additionally, the satellite also carries two experimental instruments to demonstrate new technologies: a single-frequency solid-state altimeter for the technology of low-power, low-weight altimeter and a Global Positioning System receiver for continuous,precise satellite tracking. The performance of the mission's measurement system has been tested by numerous verification studies. The results indicate that the root-sum-square accuracy of a single-pass sea level measurement is 4.7 cm for the TOPEX system and 5.1 cm for the POSEIDON system; both are more than a factor of 2 better than the requirement of 13.7 cm. This global data set is being analyzed to improve understanding of the global ocean circulation as well as the ocean tides, geodesy, and geodynamics, and ocean wind and waves. The mission is designed to last for at least 3 years with a possible extension to 6 years. The multiyear global data set will go a long way toward understanding the ocean circulation and its variability in relation to climate change. A summary of the mission's systems and their performance as well as the mission's science team is presented.

Fu, Lee-Lueng↗
DOE OSTI2022

ExaAM: Metal additive manufacturing simulation at the fidelity of the microstructure

Additive manufacturing (AM), or 3D printing, of metals is transforming the fabrication of components, in part by dramatically expanding the design space, allowing optimization of shape and topology. However, although the physical processes involved in AM are similar to those of welding, a field with decades of experimental, modeling, simulation, and characterization experience, qualification of AM parts remains a challenge. The availability of exascale computational systems, particularly when combined with data-driven approaches such as machine learning, enables topology and shape optimization as well as accelerated qualification by providing process-aware, locally accurate microstructure and mechanical property models. We describe the physics components comprising the Exascale Additive Manufacturing simulation environment and report progress using highly resolved melt pool simulations to inform part-scale finite element thermomechanics simulations, drive microstructure evolution, and determine constitutive mechanical property relationships based on those microstructures using polycrystal plasticity. We report on implementation of these components for exascale computing architectures, as well as the multi-stage simulation workflow that provides a unique high-fidelity model of process–structure–property relationships for AM parts. In addition, we discuss verification and validation through collaboration with efforts such as AM-Bench, a set of benchmark test problems under development by a team led by the National Institute of Standards and Technology.

3D printing↗
NASA NTRS2017

Risk-Significant Adverse Condition Awareness Strengthens Assurance of Fault Management Systems

As spaceflight systems increase in complexity, Fault Management (FM) systems are ranked high in risk-based assessment of software criticality, emphasizing the importance of establishing highly competent domain expertise to provide assurance. Adverse conditions (ACs) and specific vulnerabilities encountered by safety- and mission-critical software systems have been identified through efforts to reduce the risk posture of software-intensive NASA missions. Acknowledgement of potential off-nominal conditions and analysis to determine software system resiliency are important aspects of hazard analysis and FM. A key component of assuring FM is an assessment of how well software addresses susceptibility to failure through consideration of ACs. Focus on significant risk predicted through experienced analysis conducted at the NASA Independent Verification & Validation (IV&V) Program enables the scoping of effective assurance strategies with regard to overall asset protection of complex spaceflight as well as ground systems. Research efforts sponsored by NASAs Office of Safety and Mission Assurance (OSMA) defined terminology, categorized data fields, and designed a baseline repository that centralizes and compiles a comprehensive listing of ACs and correlated data relevant across many NASA missions. This prototype tool helps projects improve analysis by tracking ACs and allowing queries based on project, mission type, domain/component, causal fault, and other key characteristics. Vulnerability in off-nominal situations, architectural design weaknesses, and unexpected or undesirable system behaviors in reaction to faults are curtailed with the awareness of ACs and risk-significant scenarios modeled for analysts through this database. Integration within the Enterprise Architecture at NASA IV&V enables interfacing with other tools and datasets, technical support, and accessibility across the Agency. This paper discusses the development of an improved workflow process utilizing this database for adaptive, risk-informed FM assurance that critical software systems will safely and securely protect against faults and respond to ACs in order to achieve successful missions.

IV&V↗
DOE OSTI2020

Analysis with the ORIGEN Module of PNAR Spent Fuel Measurements for Nuclear Safeguards Applications

This report documents the analysis of the Passive Neutron Albedo Reactivity (PNAR) measurements for 23 boiling water reactor spent fuel assemblies that were performed in Finland under Action Sheet 65, which is an international collaboration on spent fuel safeguards verification methods in the context of the Finnish spent fuel encapsulation/repository system. PNAR measures the passive neutron and gamma emission rates from each of the spent fuel assemblies like a Fork detector, and it also measures the PNAR ratio, which is expected to correlate with the net neutron multiplication of the measured fuel assembly. The analysis was performed with the Oak Ridge Isotope Generation and Depletion (ORIGEN) Data Analysis Module, which was originally developed for predicting Fork detector spent fuel measurement signals in real time and has been integrated into the Integrated Review and Analysis Package developed by Euratom and the International Atomic Energy Agency. The module includes the ORIGEN burnup analysis code and integrates detector response functions pregenerated using the MCNP Monte Carlo transport code to predict the detector signals in several seconds per assembly. In this study, new response functions specific to the analyzed PNAR measurements were generated for the ORIGEN Module. The study also analyzes the impact of using detailed fuel design and operation information vs. standard safeguards information on the results calculated with the ORIGEN Module. Using detailed information reduced the standard deviation of the relative differences between calculated and measured neutron count rates among the 23 assemblies from ~10% to ~4%. The results obtained using standard safeguards information for these PNAR measurements were similar to those obtained for the Fork detector. A clear trend was found between the calculated net neutron multiplications and the measured PNAR ratios of the 23 assemblies. An uncertainty assessment of the calculations was also performed to estimate the potential impact of the accuracy and the completeness of declaration information on the calculated results for the count rates and net neutron multiplications. The ORIGEN Module predictions for PNAR signals and net neutron multiplication are expected to directly support the safeguards inspectors’ efforts to verify operator declarations of a spent fuel assembly in real time in safeguards practices.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS2018

Dynamic Power Convertor Development for Radioisotope Power Systems at NASA GRC

The Thermal Energy Conversion Branch at NASA Glenn Research Center (GRC) is supporting the development of high-efficiency power convertors in support of Radioisotope Power System (RPS) development. Significant progress was made towards such a system that utilized Stirling conversion machines during the 2001 to 2015 timeframe. Flight development of the Advanced Stirling Radioisotope Generator (ASRG) was cancelled in 2013 by the Department of Energy (DOE) and NASA Headquarters primarily due to budget constraints, and the Advanced Stirling Convertor (ASC) technology contract was subsequently concluded in 2015. A new chapter of technology development has recently been initiated by the NASA RPS Program. This new effort is considering all dynamic power convertor options, such as Stirling and Brayton cycles. Four convertor development contracts supporting this effort were awarded in 2017. The awarded contracts include two free-piston Stirling, one thermoacoustic Stirling, and one turbo-Brayton designs. The technology development contracts each consist of up to three phases: Design, Fabricate, and Test. As of May 2018, all contracts have completed the Design Phase, and each underwent a design review with an independent review board. Two of the contracts have been awarded the Phase 2 option for fabrication. Convertors manifesting from these development efforts will then undergo independent validation and verification at NASA facilities, which will consist of convertor performance and RPS viability demonstrations. Example tests include launch vibration simulation, performance mapping over the environmental temperature range, and static acceleration exposure. In parallel with this renewed development effort, NASA GRC is still demonstrating free-piston Stirling convertor technology using assets from previous projects. The Stirling Research Laboratory (SRL) is still operating 10 convertors from previous development projects. Four of which are flexure-bearing based, and the other six are gas-bearing based. One of the flexure-bearing convertors has accumulated over 110,000 hours of operation, and holds the current maintenance-free heat-engine run-time record. Another flexure-bearing convertor was recently manually shutdown after 105,620 hours of operation, then disassembled and inspected. This inspection produced a wealth of information about the effects of this amount of runtime on the technology's components. One of the engineering unit flexure-bearing convertors recently underwent launch simulation vibration test, a static acceleration exposure up to 20 g, and was then placed on extended operation. Amongst the gas-bearing convertors, the longest running unit has accumulated over 70,000 hours of operation. Four high-fidelity gas-bearing convertors from the ASRG project are still operating continuously, for which the longest runtime has reached 26,000 hours.

Oriti, Salvatore↗
NASA NTRS2008

From Informal Safety-Critical Requirements to Property-Driven Formal Validation

Most of the efforts in formal methods have historically been devoted to comparing a design against a set of requirements. The validation of the requirements themselves, however, has often been disregarded, and it can be considered a largely open problem, which poses several challenges. The first challenge is given by the fact that requirements are often written in natural language, and may thus contain a high degree of ambiguity. Despite the progresses in Natural Language Processing techniques, the task of understanding a set of requirements cannot be automatized, and must be carried out by domain experts, who are typically not familiar with formal languages. Furthermore, in order to retain a direct connection with the informal requirements, the formalization cannot follow standard model-based approaches. The second challenge lies in the formal validation of requirements. On one hand, it is not even clear which are the correctness criteria or the high-level properties that the requirements must fulfill. On the other hand, the expressivity of the language used in the formalization may go beyond the theoretical and/or practical capacity of state-of-the-art formal verification. In order to solve these issues, we propose a new methodology that comprises of a chain of steps, each supported by a specific tool. The main steps are the following. First, the informal requirements are split into basic fragments, which are classified into categories, and dependency and generalization relationships among them are identified. Second, the fragments are modeled using a visual language such as UML. The UML diagrams are both syntactically restricted (in order to guarantee a formal semantics), and enriched with a highly controlled natural language (to allow for modeling static and temporal constraints). Third, an automatic formal analysis phase iterates over the modeled requirements, by combining several, complementary techniques: checking consistency; verifying whether the requirements entail some desirable properties; verify whether the requirements are consistent with selected scenarios; diagnosing inconsistencies by identifying inconsistent cores; identifying vacuous requirements; constructing multiple explanations by enabling the fault-tree analysis related to particular fault models; verifying whether the specification is realizable.

Cimatti, Alessandro↗
NASA NTRS2017

Compact piezoelectric resonance mass balance for sample verification and mass quantification and mixing.

There is a need for sample verification and mass quantification of rock, soil and/or ice obtained by sample acquisition mechanisms on extraterrestrial bodies. For many scientific instruments information about the mass of the sample would aid in the interpretation of the data and help prevent the portioning system from overloading instrument ports. Additionally, on a potential sample return mission it is likely that a sample confirmation or mass determination requirement would be implemented before the spacecraft would be commanded to return to Earth or Lunar orbit. In an effort to meet these potential requirements, a piezoelectric resonance balance is being developed to measure a frequency change proportional to the sample mass change. In previous work1 we developed a resonance balance which produced large non-linear frequency changes due to the addition of a large mass. In this study we have looked at a variety of resonator geometries in an effort to linearize the frequency shift with mass. In addition, we have investigated the use of oscillator/counter circuitry to track the frequency shift of the piezoelectric mass balance. In this new design the frequency shifts automatically when a mass is placed on the balance and the counter circuit calculates the frequency shift. This frequency is then converted to a mass using calibration tables determined previously. An additional feature we have implemented is the use of a high frequency thickness mode piezoelectric resonator to mix the sample and a reactant or solvent. This allows for measuring both sample and reagent prior to ingestion by the instrument. This paper will focus on the design requirements and how they are affected by the local gravity and acoustic properties of the sample. Designs which allow for easy loading and unloading of the balance will also be discussed.

Yahnker, Christopher R.↗
DOE OSTI2025

Web-Based Tools for Data-Informed Remedy Optimization: Software Theory and User Guide

This report documents the development and application of two web-based decision-support tools for pump-and-treat (P&T) groundwater remediation systems: PTOLEMY (Pump-and-Treat Optimized Location Evaluation to Maximize Yields) and OPTIMA (Optimization for Pump-and-Treat Implementation, Management, & Assessment). These tools enhance remedy design and management by leveraging advanced computational methods – specifically deep learning and multi-objective optimization – within a user-friendly platform. By integrating data-driven models with established hydrogeological knowledge, PTOLEMY and OPTIMA enable more efficient evaluation of well placement and operational strategies, helping site managers balance multiple remediation objectives under complex conditions. Both tools are implemented as modules within the SOCRATES (Suite Of Comprehensive Rapid Analysis Tools for Environmental Sites) web platform, which provides data access, visualization, and analytics to support remedy optimization across sites in the U.S. Department of Energy Office of Environmental Management complex. PTOLEMY is a rapid screening module designed to identify promising locations for new extraction wells. It employs a multi-channel three-dimensional convolutional neural network (MC3D-CNN) trained on high-fidelity simulation data to predict the relative performance (in terms of contaminant mass recovery) of potential well sites. Through an interactive web interface, PTOLEMY visualizes the probability of high performance across a site, highlighting areas where an extraction well is likely to yield above-threshold contaminant removal over a multi-year period. PTOLEMY’s map-based displays and exportable results support transparent communication of screening analyses. By focusing attention on the most favorable candidate locations, the tool augments traditional engineering judgment and physics-based modeling, providing a data informed basis for subsequent detailed evaluations. OPTIMA is a multi objective optimization module designed to find wellfield layouts and operating schedules that meet various cleanup goals. It quickly evaluates thousands of candidate setups – combinations of well locations, timing, and rates – and returns a small set of best trade-off options for comparison. At its core, OPTIMA uses a U-Net-based surrogate model – a deep-learning emulator of a groundwater flow and transport simulator – to dramatically accelerate scenario evaluations. Coupling this fast surrogate with the NSGA-II (Non-dominated Sorting Genetic Algorithm II) evolutionary algorithm, OPTIMA explores a wide decision space of well locations and schedules to identify Pareto-optimal solutions that trade off key objectives (e.g., minimizing cleanup time, maximizing contaminant mass removal, and minimizing plume extent). The tool outputs a family of optimal configurations and visualizes their trade-offs (Pareto frontiers of cleanup metrics and maps of optimized well placements). Site managers can use these results to understand the range of viable strategies and to select candidate designs for more detailed verification. OPTIMA is currently under active development and not yet fully released; this guide provides early documentation to support planning and gather user feedback.

54 ENVIRONMENTAL SCIENCES↗