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Lorentz invariant theory for relativistic gravity testing, deriving conservation laws and parameter constraints from parametrized post-Newtonian equations of motion
Metric theories of gravity are compiled and classified according to the types of gravitational fields they contain, and the modes of interaction among those fields. The gravitation theories considered are classified as (1) general relativity, (2) scalar-tensor theories, (3) conformally flat theories, and (4) stratified theories with conformally flat space slices. The post-Newtonian limit of each theory is constructed and its Parametrized Post-Newtonian (PPN) values are obtained by comparing it with Will's version of the formalism. Results obtained here, when combined with experimental data and with recent work by Nordtvedt and Will and by Ni, show that, of all theories thus far examined by our group, the only currently viable ones are general relativity, the Bergmann-Wagoner scalar-tensor theory and its special cases (Nordtvedt; Brans-Dicke-Jordan), and a recent, new vector-tensor theory by Nordtvedt, Hellings, and Will.
The post-Newtonian limit of Rosen's theory of gravity is evaluated and is shown to be identical to that of general relativity, except for the PPN parameter alpha sub 2, which is related to the difference in propagation speeds for gravitational and electromagnetic waves. Both the value of alpha sub 2 and the value of the Newtonian gravitational constant depend on the present cosmological structure of the Universe. If the cosmological structure has a specific but presumably special form, the Newtonian gravitational constant assumes its current value, alpha sub 2 is zero, the post-Newtonian limit of Rosen's theory is identical to that of general relativity--and standard solar system experiments cannot distinguish between the two theories.
The post-Newtonian limit of Rosen's theory of gravity is evaluated and is shown to be identical to that of general relativity, except for the post-Newtonian parameter alpha sub 2 (which is related to the difference in propagation speeds for gravitational and electromagnetic waves). Both the value of alpha sub 2 and the value of the Newtonian gravitational constant depend on the present cosmological structure of the Universe. If the cosmological structure has a specific (but presumably special) form, the Newtonian gravitational constant assumes its current value, alpha sub 2 is zero, the post-Newtonian limit of Rosen's theory is identical to that of general relativity - and standard solar system experiments cannot distinguish between the two theories.
America's electrical grid is currently undergoing a multi-billion dollar modernization effort aimed at producing a highly reliable critical national infrastructure for power - a Smart Grid. While the goals for the Smart Grid include upgrades to accommodate large quantities of clean, but transient, renewable energy and upgrades to provide customers with real-time pricing information, perhaps the most important objective is to create an electrical grid with a greatly increased robustness.
The Advanced Supersonic Parachute Inflation Research Experiment-2 (ASPIRE2) program is designed to test and qualify the supersonic parachute for the Mars entry, descent, and landing stage of the Mars Sample Return campaign. The ASPIRE2 test was planned for early 2026 and would have involved testing the parachute at deployments of Mach 2.1 and higher load conditions than previous Mars missions. The ASPIRE2 simulation builds upon a previous test framework from the ASPIRE tests in 2017-2018 used to qualify the Mars 2020 parachute, but due to new requirements, the modeling and simulation for ASPIRE2 has needed development and characterization of different sensitivities. This paper looks at the mission design as of mid-2024 and presents the trade space for qualifying the parachute in a dynamic environment.
The Advanced Supersonic Parachute Inflation Research Experiment-2 (ASPIRE2) program is designed to test and qualify the supersonic parachute for the Mars entry, descent, and landing stage of the Mars Sample Return campaign. The ASPIRE2 test was planned for early 2026 and would have involved testing the parachute at deployments of Mach 2.1 and higher load conditions than previous Mars missions. The ASPIRE2 simulation builds upon a previous test framework from the ASPIRE tests in 2017-2018 used to qualify the Mars 2020 parachute, but due to new requirements, the modeling and simulation for ASPIRE2 has needed development and characterization of different sensitivities. This paper looks at the mission design as of mid-2024 and presents the trade space for qualifying the parachute in a dynamic environment.
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The Scalable Checkpoint/Restart library (SCR) was developed and is used by researchers at Lawrence Livermore National Laboratory to provide a fast and efficient method of saving and recovering large applications during runtime on high-performance computing (HPC) systems. Though SCR protects other programs, up until June 2017, nothing was actively protecting SCR. The goal of this project was to automate the building and testing of this library on the varying HPC architectures on which it is used. Our methods centered around the use of a continuous integration tool called Bamboo that allowed for automation agents to be installed on the HPC systems themselves. These agents provided a way for us to establish a new and unique way to automate and customize the allocation of resources and running of tests with CMake’s unit testing framework, CTest, as well as integration testing scripts though an HPC package manager called Spack. These methods provided a parallel environment in which to test the more complex features of SCR. As a result, SCR is now automatically built and tested on several HPC architectures any time changes are made by developers to the library’s source code. The results of these tests are then communicated back to the developers for immediate feedback, allowing them to fix functionality of SCR that may have broken. Hours of developers’ time are now being saved from the tedious process of manually testing and debugging, which saves money and allows the SCR project team to focus their efforts towards development. Thus, HPC system users can use SCR in conjunction with their own applications to efficiently and effectively checkpoint and restart as needed with the assurance that SCR itself is functioning properly.
To support the National Aeronautics and Space Administration’s (NASA) Space Launch System (SLS) rocket and the Orion capsule, designed to take humans back to the moon in 2024, Kennedy Space Center (KSC) has developed the Spaceport Command and Control System (SCCS) to monitor and control the launch. Within SCCS, the Launch Control System (LCS) is designed to allow console engineers to control and monitor the status of the launch and flight hardware, as well as issue commands to ground control systems and launch vehicles. The messaging software of LCS is responsible for handling the various data types that can be sent between the hardware and software components of the LCS. Since this system is interacting with numerous devices, controllers, and viewports in real time, the distribution of data across the system must be fast, but also reliable and accurate. To verify the accuracy and reliability of the system, developers on the project have created a set of tests to be performed that covers all operations allowed by the system. Given the extensive Application Programming Interface(API) provided by the messaging software, these unit tests are rather time-consuming and costly (in terms of man-hours) to perform. Therefore, an automated testing framework is used to perform supplemental tests automatically when updates are made to the code base.
The R-Matrix code SAMMY is a widely used nuclear data evaluation code focused on the resolved range, which includes corrections for experimental effects. The code is still mostly written in Fortran 77, and uses a memory management system suitable for the time of its initial writing (1984). A modernization effort is under way to bring the code in-line with modern software development practices. A continuous-integration testing framework was added, automating the large existing set of test cases. It is run on every commit. The memory management was updated to current standard practices suitable for modern software analysis tools. The code can be obtained from https://code.ornl.gov/RNSD/SAMMY. The resonance parameters and covariance information are now stored in C++ objects shared by SAMMY and AMPX, the processing code that generates nuclear data libraries for SCALE. This allows for easier maintenance and access to the resonance parameters inside and outside of SAMMY. This feature is already used by accessing and changing parameters in memory in the Bayesian Monte Carlo Evaluation Framework for Cross Sections Nuclear Data and Integral Benchmark Experiments project, Further plans include the switch to the ENDF reading and writing routines in AMPX, as these routines are more robust, easier to maintain, and support more features. Of note here is support for the new GNDS format. Previously it wasn’t easy to share the full covariance matrix for evaluations containing more than one isotope due to limitations on the ENDF format; this is now supported in GNDS. The data are currently available in a binary SAMMY format and can be exported to GNDS to make them more widely available and sharable. The next step will be to use the same resonance processing code at 0K in AMPX and SAMMY as one of the available Reich-Moore R-Matrix formalism. The first step toward this goal is to isolate the reconstruction into a module that takes resonance parameters as its input and does not depend on SAMMY global parameters. This goal has been achieved and it should now be possible to more easily change the resonance formalism and add enhancements as the Phenomenological R-Matrix parameterization of direct, doorway, and compound nuclear reactions discussed elsewhere on this conference. This concerted modernization and enhancement effort provides multiple advantages to the nuclear data community. It will allow parameter optimization using enhanced formalisms, including experimental effects, that better match complex experimental data. Then those evaluated parameters can immediately be passed off to AMPX to be reconstructed with the exact same cross section model and be put into a data library for subsequent testing using SCALE and the Valid Benchmark suite or other suitable benchmark suites.
This tutorial will introduce Fortran developers to unit-testing and test-driven development (TDD) using pFUnit. As with other unit-testing frameworks, pFUnit, simplifies the process of writing, collecting, and executing tests while providing clear diagnostic messages for failing tests. pFUnit specifically targets the development of scientific-technical software written in Fortran and includes customized features such as: assertions for multi-dimensional arrays, distributed (MPI) and thread-based (OpenMP) parallellism, and flexible parameterized tests.These sessions will include numerous examples and hands-on exercises that gradually build in complexity. Attendees are expected to have working knowledge of F90, but familiarity with object-oriented syntax in F2003 and MPI will be of benefit for the more advanced examples. By the end of the tutorial the audience should feel comfortable in applying pFUnit within their own development environment.
BLT bundles custom CMake macros, unit testing frameworks for C++ and Fortran, and a set of smoke tests for common HPC dependencies. The combination of these three provides a foundation for quickly bootstrapping a CMale-based system for developing HPC softward.
Developers working in Computational Science & Engineering (CSE)/High Performance Computing (HPC) must contend with constant change due to advances in computing technology and science. Test Driven Development (TDD) is a methodology that mitigates software development risks due to change at the cost of adding comprehensive and continuous testing to the development process. Testing frameworks tailored for CSE/HPC, like pFUnit, can lower the barriers to such testing, yet CSE software faces unique constraints foreign to the broader software engineering community. Effective testing of numerical software requires a comprehensive suite of oracles, i.e., use cases with known answers, as well as robust estimates for the unavoidable numerical errors associated with implementation with finite-precision arithmetic. At first glance these concerns often seem exceedingly challenging or even insurmountable for real-world scientific applications. However, we argue that this common perception is incorrect and driven by (1) a conflation between model validation and software verification and (2) the general tendency in the scientific community to develop relatively coarse-grained, large procedures that compound numerous algorithmic steps.We believe TDD can be applied routinely to numerical software if developers pursue fine-grained implementations that permit testing, neatly side-stepping concerns about needing nontrivial oracles as well as the accumulation of errors. We present an example of a successful, complex legacy CSE/HPC code whose development process shares some aspects with TDD, which we contrast with current and potential capabilities. A mix of our proposed methodology and framework support should enable everyday use of TDD by CSE-expert developers.
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Digital Instrumentation and Control Systems (ICSs) have replaced analog control systems in nuclear power plants raising cybersecurity concerns. To study and understand the cybersecurity risks of nuclear power plants both high fidelity models of the plant physics and controllers must be created, and a framework to test and evaluate cyber security events must be established. A testing and evaluation framework of cybersecurity events consists of a method of interfering with control systems, a simulation of the plant network, and a network packet capture and recording tool. Sandia National Labs (SNL) in collaboration with the University of New Mexico’s Institute for Space and Nuclear Power Studies (UNM-ISNPS) is developing such a cybersecurity testing framework.
Pyctos is a concolic testing framework for standard, dynamically-typed Python. Pyctos is able to generate exhaustive test inputs reaching 100% coverage for a subset of pure Python in the absence of type annotations, even where modern fuzzers would fail. Pyctos's underlying reasoning engine is the CVC5 SMT solver, though Z3 is also supported. Pyctos also supports a growing subset of the standard library and some third-party libraries, such as NumPy.