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The Cassini spacecraft, NASA's mission to investigate the Saturn system, has undergone a system-level thermal balance test program to permit verification of the science instrument thermal designs in the simulated worst-case environments.
The Cassini spacecraft, NASA's mission to investigate the Saturn system, has undergone a system level themal balance test program to permit verification of the engineering subsystem themal designs in the simulated worst-case environments.
On February 18th, 2021, the Mars 2020 project's Perseverance Rover successfully touched down on the Martian surface after nearly eight years of development. The Mars 2020 Entry, Descent, and Landing (EDL) System largely leveraged heritage from the Mars Science Laboratory (MSL) EDL System while employing targeted technological advancements. The landing process is autonomously directed by a software behavior implemented in the rover's primary flight computer called the EDL Timeline that assumes control of the vehicle six days before atmospheric entry. This paper first walks through the basics of the EDL Timeline mechanics and how the behavior is designed to account for internal system variations and environmental unknowns. It then summarizes the interactions between the EDL timeline and other high-level system behaviors like spacecraft mode transitions and system fault protection, focusing on the complications that arise when passing spacecraft control between executive functions. Although the MSL-inherited EDL System is reliable and capable, targeted updates and a thorough verification and validation program were required for Mars 2020. This paper discusses changes made to close vulnerabilities discovered during both MSL and Mars 2020 development cycles, landing system capability enhancements that were enabling for Mars 2020's mission, and how these updates were integrated with the heritage system. It then describes how both analysis and testing campaigns were utilized to verify and validate all aspects of EDL and system behaviors that run during the six days before landing, as well as the operational workarounds that were needed to address problems found during the development and commissioning process. Finally, this paper imparts lessons learned from Mars 2020 EDL development, implementation, and operations, emphasizing how systems designed to conduct time-critical mission events with low margin of error can be improved in the future.
On February 18th, 2021, the Mars 2020 project's Perseverance Rover successfully touched down on the Martian surface after nearly eight years of development. The Mars 2020 Entry, Descent, and Landing (EDL) System largely leveraged heritage from the Mars Science Laboratory (MSL) EDL System while employing targeted technological advancements. The landing process is autonomously directed by a software behavior implemented in the rover's primary flight computer called the EDL Timeline that assumes control of the vehicle six days before atmospheric entry. In addition to performing the critical function of landing the rover on the Martian surface, the EDL timeline behavior must co-exist in a non-partitioned software and system environment with other high-level functions that accomplish the goals for the rest of the mission. Due to the criticality of EDL, the potential for loss of mission, and a need for complete system autonomy, the standard for how the EDL Timeline interacts with other functions in the system is highly constrained. This paper first walks through the basics of the EDL Timeline mechanics and how the behavior is designed to account for internal system variations and environmental unknowns. It then summarizes the interactions between the EDL timeline and other high-level system behaviors like spacecraft mode transitions and system fault protection, focusing on the complications that arise when passing spacecraft control between executive functions. Although the MSL-inherited EDL System is reliable and capable, targeted updates and a thorough verification and validation program were required for Mars 2020. This paper discusses changes made to close vulnerabilities discovered during both MSL and Mars 2020 development cycles, landing system capability enhancements that were enabling for Mars 2020's mission, and how these updates were integrated with the heritage system. It then describes how both analysis and testing campaigns were utilized to verify and validate all aspects of EDL and system behaviors that run during the six days before landing, as well as the operational workarounds that were needed to address problems found during the development and commissioning process. Finally, this paper imparts lessons learned from Mars 2020 EDL development, implementation, and operations, emphasizing how systems designed to conduct time-critical mission events with low margin of error can be improved in the future.
Transcriptomics holds significant value in elucidating the relationship between gene expression, experimental factors, biological factors, and various types of omics data. Enhancing our understanding of these connections is paramount for foundational biology, which plays a pivotal role in devising solutions for challenges pertinent to both space travel and terrestrial life. The NASA GeneLab project, part of the Open Science Data Repository (OSDR.nasa.gov), seeks to accelerate space biology research through cataloging and democratizing ‘omics data, including transcriptomics. Since raw omics data are largely inaccessible to non-bioinformaticians, GeneLab works with the scientific community via the Open Science Analysis Working Groups (AWGs) to develop standard processing pipelines to generate and publish processed data. Unlike raw data, processed data have greater immediate value to diverse users with varying technical backgrounds and computational capabilities. Standardizing processing workflows is essential to match the pace of raw data generation, ensure reproducibility, and enable standardized processed data for comparison across datasets. As of June 2023, transcriptomics studies comprise over half of GeneLab datasets hosted on the OSDR, including data from bulk RNA-seq and Affymetrix or Agilent 1-Channel DNA microarray assays. In collaboration with the AWGs, GeneLab developed consensus processing pipelines for these transcriptomics data types that includes quality control, background correction (microarray only), data normalization and quantification, culminating in the detection and annotation of differentially expressed genes. The work presented here describes Nextflow implementations of GeneLab’s consensus transcriptomics pipelines that automates and accelerates processing of these datasets. In addition to the core data processing, these workflows also include raw data staging and a robust verification and validation program to identify errors in real-time, stop additional downstream computation, and preserve computational resources. These workflows are used to generate GeneLab processed data hosted on the OSDR, and are publicly available as open source software for others to use at: https://github.com/nasa/GeneLab_Data_Processing.
An integrated set of tools called a validation environment is proposed to support the validation of Ada programs by a combination of methods. A Modular Ada Validation Environment (MAVEN) is described which proposes a context in which formal verification can fit into the industrial development of Ada software.
In 2010, NASA established the Commercial Crew Program in order to provide human access to the International Space Station and low earth orbit via the commercial (non-governmental) sector. A particular challenge to NASA has been how to determine the commercial providers transportation system complies with Programmatic safety requirements. The process used in this determination is the Safety Technical Review Board which reviews and approves provider submitted Hazard Reports. One significant product of the review is a set of hazard control verifications. In past NASA programs, 100 percent of these safety critical verifications were typically confirmed by NASA. The traditional Safety and Mission Assurance (SMA) model does not support the nature of the Commercial Crew Program. To that end, NASA SMA is implementing a Risk Based Assurance (RBA) process to determine which hazard control verifications require NASA authentication. Additionally, a Shared Assurance Model is also being developed to efficiently use the available resources to execute the verifications. This paper will describe the evolution of the CCP Mission Assurance process from the beginning of the Program to its current incarnation. Topics to be covered include a short history of the CCP; the development of the Programmatic mission assurance requirements; the current safety review process; a description of the RBA process and its products and ending with a description of the Shared Assurance Model.
The National Aeronautics and Space Administration (NASA), through its Technology Utilization Program, has been making its advanced technology developments available to the public. This has coincided in recent years with a growing demand within the fire service for improved protective equipment. A better breathing system for firefighters was one of the more immediate needs identified by the firefighting organizations. The Johnson Space Center (JSC), based upon their experience in providing life support systems for space flight, was subsequently requested to determine the feasibility of providing an improved breathing system for firefighters. Such a system was determined to be well within the current state of the art, and the Center is well into a development program to provide design verification of this improved protective' equipment. This report - outlines the overall objectives of this program, progress to date, and future planned activities.
The Multibody Modeling, Verification, and Control (MMVC) Laboratory is under development at NASA MSFC in Huntsville, Alabama. The laboratory will provide a facility in which dynamic tests and analyses of multibody flexible structures representative of future space systems can be conducted. The purpose of the tests are to acquire dynamic measurements of the flexible structures undergoing large angle motions and use the data to validate the multibody modeling code, TREETOPS, developed under sponsorship of NASA. Advanced control systems design and system identification methodologies will also be implemented in the MMVC laboratory. This paper describes the ground test facility, the real-time control system, and the experiments. A top-level description of the TREETOPS code is also included along with the validation plan for the MMVC program. Dynamic test results from component testing are also presented and discussed. A detailed discussion of the test articles, which manifest the properties of large flexible space structures, is included along with a discussion of the various candidate control methodologies to be applied in the laboratory.
In 2010, the National Aeronautics and Space Administration (NASA) established the Commercial Crew Program (CCP) in order to provide human access to the International Space Station and low Earth orbit via the commercial (non-governmental) sector. A particular challenge to NASA has been how to determine that the Commercial Provider's transportation system complies with programmatic safety requirements. The process used in this determination is the Safety Technical Review Board which reviews and approves provider submitted hazard reports. One significant product of the review is a set of hazard control verifications. In past NASA programs, 100% of these safety critical verifications were typically confirmed by NASA. The traditional Safety and Mission Assurance (S&MA) model does not support the nature of the CCP. To that end, NASA S&MA is implementing a Risk Based Assurance process to determine which hazard control verifications require NASA authentication. Additionally, a Shared Assurance Model is also being developed to efficiently use the available resources to execute the verifications.
A research program in spacecraft structures, structural dynamics, and controls verification using a relatively large, flexible beam as a focus is introduced. This research effort addresses fundamental problems applicable to the verification of large, flexible space structures and combines ground tests, flight behavior prediction, and instrumented orbital tests. The program is expected to produce quantitative results for use in improving the validity of ground tests for verifying flight performance analyses.
Methodologies are discussed on four of the major approaches to program upgrading -- namely dynamic testing, symbolic execution, formal verification and static analysis. The different patterns of strengths, weaknesses and applications of these approaches are shown. It is demonstrated that these patterns are in many ways complementary, offering the hope that they can be coordinated and unified into a single comprehensive program testing and verification system capable of performing a diverse and useful variety of error detection, verification and documentation functions.
Regression verification techniques are used to prove equivalence of syntactically similar programs. Checking equivalence of large programs, however, can be computationally expensive. Existing regression verification techniques rely on abstraction and decomposition techniques to reduce the computational effort of checking equivalence of the entire program. These techniques are sound but not complete. In this work, we propose a novel approach to improve scalability of regression verification by classifying the program behaviors generated during symbolic execution as either impacted or unimpacted. Our technique uses a combination of static analysis and symbolic execution to generate summaries of impacted program behaviors. The impact summaries are then checked for equivalence using an o-the-shelf decision procedure. We prove that our approach is both sound and complete for sequential programs, with respect to the depth bound of symbolic execution. Our evaluation on a set of sequential C artifacts shows that reducing the size of the summaries can help reduce the cost of software equivalence checking. Various reduction, abstraction, and compositional techniques have been developed to help scale software verification techniques to industrial-sized systems. Although such techniques have greatly increased the size and complexity of systems that can be checked, analysis of large software systems remains costly. Regression analysis techniques, e.g., regression testing [16], regression model checking [22], and regression verification [19], restrict the scope of the analysis by leveraging the differences between program versions. These techniques are based on the idea that if code is checked early in development, then subsequent versions can be checked against a prior (checked) version, leveraging the results of the previous analysis to reduce analysis cost of the current version. Regression verification addresses the problem of proving equivalence of closely related program versions [19]. These techniques compare two programs with a large degree of syntactic similarity to prove that portions of one program version are equivalent to the other. Regression verification can be used for guaranteeing backward compatibility, and for showing behavioral equivalence in programs with syntactic differences, e.g., when a program is refactored to improve its performance, maintainability, or readability. Existing regression verification techniques leverage similarities between program versions by using abstraction and decomposition techniques to improve scalability of the analysis [10, 12, 19]. The abstractions and decomposition in the these techniques, e.g., summaries of unchanged code [12] or semantically equivalent methods [19], compute an over-approximation of the program behaviors. The equivalence checking results of these techniques are sound but not complete-they may characterize programs as not functionally equivalent when, in fact, they are equivalent. In this work we describe a novel approach that leverages the impact of the differences between two programs for scaling regression verification. We partition program behaviors of each version into (a) behaviors impacted by the changes and (b) behaviors not impacted (unimpacted) by the changes. Only the impacted program behaviors are used during equivalence checking. We then prove that checking equivalence of the impacted program behaviors is equivalent to checking equivalence of all program behaviors for a given depth bound. In this work we use symbolic execution to generate the program behaviors and leverage control- and data-dependence information to facilitate the partitioning of program behaviors. The impacted program behaviors are termed as impact summaries. The dependence analyses that facilitate the generation of the impact summaries, we believe, could be used in conjunction with other abstraction and decomposition based approaches, [10, 12], as a complementary reduction technique. An evaluation of our regression verification technique shows that our approach is capable of leveraging similarities between program versions to reduce the size of the queries and the time required to check for logical equivalence. The main contributions of this work are: - A regression verification technique to generate impact summaries that can be checked for functional equivalence using an off-the-shelf decision procedure. - A proof that our approach is sound and complete with respect to the depth bound of symbolic execution. - An implementation of our technique using the LLVMcompiler infrastructure, the klee Symbolic Virtual Machine [4], and a variety of Satisfiability Modulo Theory (SMT) solvers, e.g., STP [7] and Z3 [6]. - An empirical evaluation on a set of C artifacts which shows that the use of impact summaries can reduce the cost of regression verification.
Objectives of the Optimal and Nominal Nuclear-Testing Programs: Define optimal and nominal nuclear-testing programs; Discuss underground development for nuclear operations; Discuss underground nuclear operations, safety, and health; Compare drift complexes of optimal and nominal testing programs; Compare drift complexes for nuclear testing and commercial production; Discuss a potential future look of underground development and operations.
The paper presents a compilation of the results of a systems level Shuttle/payload contamination analysis and related computer modeling activities. The current technical assessment of the contamination problems anticipated during the Spacelab program are discussed and recommendations are presented on contamination abatement designs and operational procedures based on experience gained in the field of contamination analysis and assessment, dating back to the pre-Skylab era. The ultimate test of the Shuttle/Payload Contamination Evaluation program will be through comparison of predictions with measured levels of contamination during actual flight.
The results of a NASA SBIR project are presented in which CSP-Ariel, a verification system for C programs which use Unix system calls for concurrent programming, interprocess communication, and file input and output, was developed. This project builds on ORA's Ariel C verification system by using the system of Hoare's book, Communicating Sequential Processes, to model concurrency and communication. The system runs in ORA's Clio theorem proving environment. The use of CSP to model Unix concurrency and sketch the CSP semantics of a simple concurrent program is outlined. Plans for further development of CSP-Ariel are discussed. This paper is presented in viewgraph form.
As part of the regular nuclear material accounting and control process, sites that have accountable nuclear material regularly perform measurements of the material in their possession. The expectation for the type of measurements and their frequency is set out in Department of Energy (DOE) Order 474.2, and further detailed in each site’s respective material control and accountability (MC&A) plan and associated controlling documents. The measurements of interest in this report are those performed on external (between DOE sites) transfer receipts of Category III or IV accountable materials. In 2020, a revision of DOE Order 474.2 was proposed that would significantly increase the requirement that measurements be performed upon receipt of material, and further, that those measurements be quantitative verification (rather than qualitative confirmatory) measurements. A survey was performed of DOE sites to discuss the impact on their MC&A measurements program if more rigorous verification measurements requirements for Category III and IV receipts were implemented. An assessment of nondestructive assay (NDA) measurement instruments to meet those needs was also performed. Across the board, sites indicated that personnel and budget would cause the largest impact. Sites which are qualified as Category I/II indicated a reduced impact as these sites already have the measurement capabilities and some personnel but would require the acquisition of additional measurement systems. Category III/IV sites indicated a much larger impact as these sites generally have smaller MC&A programs. A few smaller sites stated a measurement program would need to be created to handle the demand. Calorimetry, quantitative gamma spectroscopy and neutron coincidence counting systems were identified as common systems that could meet the verification measurement requirements. The other, and perhaps larger issue is the need for calibration standards for the calorimetry and neutron coincidence counting systems. It is proposed that a comparative study be performed for ISOCS and ISOTOPICS, qualification of a COTS calorimetry system be performed, and development of an AWCC system that uses a neutron generator.
The NASA Goddard Space Flight Center s General Environmental Verification Specification (GEVS) for STS and ELV Payloads, Subsystems, and Components is currently being revised based on lessons learned from GSFC engineering and flight assurance. The GEVS has been used by Goddard flight projects for the past 17 years as a baseline from which to tailor their environmental test programs. A summary of the requirements and updates are presented along with the rationale behind the changes. The major test areas covered by the GEVS include mechanical, thermal, and EMC, as well as more general requirements for planning, tracking of the verification programs.