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DOE OSTI2025

Factors That Influence Variability in Stress-Drop Measurements Using Spectral Decomposition and Spectral-Ratio Methods for the 2019 Ridgecrest Earthquake Sequence

Stress drop is a fundamental parameter related to earthquake source physics, but is hard to measure accurately. To better understand how different factors influence stress-drop measurements, we compare two different methods using the Ridgecrest stress-drop validation data set: spectral decomposition (SD) and spectral ratio (SR), each with different processing options. Here, we also examine the influence of spectral complexity on source parameter measurement. Applying the SD method, we find that frequency bandwidth and time-window length could influence spectral magnitude calibration, while depth-dependent attenuation is important to correctly map stress-drop variations. For the SR method, we find that the selected source model has limited influence on the measurements; however, the Boatwright model tends to produce smaller standard deviation and larger magnitude dependence than the Brune model. Variance reduction threshold, frequency bandwidth, and time-window length, if chosen within an appropriate parameter range, have limited influence on source parameter measurement. For both methods, wave type, attenuation correction, and spectral complexity strongly influence the result. The scale factor that quantifies the magnitude dependence of stress drop show large variations with different processing options, and earthquakes with complex source spectra deviating from the Brune-type source models tend to have larger scale factor than earthquakes without complexity. Based on these detailed comparisons, we make a few specific suggestions for data processing workflows that could help future studies of source parameters and interpretations.

58 GEOSCIENCES↗

DOE OSTI2022

The role of surface forces in environment-enhanced cracking of brittle solids

Fracture initiation and propagation in brittle materials is promoted in surface-reactive (sorptive) environments, a phenomenon known as subcritical crack growth (SCG). Laboratory measured crack-propagation velocity vs. stress intensity factor relationships typically exhibit highly nonlinear, multi-stage characteristics that are sensitive to environmental factors such as adsorbate concentration and temperature. For practical purposes, empirical relationships (e.g., a power law) have been used to describe this complex phenomenon. However, how the overall SCG behavior emerges from the underlying fundamental processes near the crack tip, such as the interaction of the crack surfaces separated by only a few nanometers and mass transport within the nano-confined space, is still not well understood. This paper develops a mechanistic, surface-force-based fracture theory (SFFT) which integrates surface force models, fluid transport models, and linear elastic fracture mechanics to quantitatively explain the multi-stage characteristics of SCG in brittle solids. A numerical model is developed based on SFFT and solved through an implicit partitioned scheme for efficiency and modularity. The results are validated by Wiederhorn's data on crack propagation in soda-lime glasses at a wide range of relative humidity levels. We show that, for the first time, the entire range of an SCG curve can be captured by a single physics-based model. The predicted SCG curves reveal that the development of repulsive disjoining pressure behind the crack tip can be responsible for the reduced apparent fracture toughness in a sorptive environment. In conclusion, the shape of the SCG curve, and its changes with respect to the environment, is found to critically depend on the assumed transport models.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Field, frequency, and temperature dependencies of the surface resistance of nitrogen diffused niobium superconducting radio frequency cavities

We investigate the rf performance of several single-cell superconducting radio-frequency cavities subjected to low temperature heat treatment in nitrogen environment. The cavities were treated at temperature 120 – 165 ° C for an extended period of time (24–48 h) either in high vacuum or in a low partial pressure of ultrapure nitrogen. The improvement in Q 0 with a Q rise was observed when nitrogen gas was injected at ∼ 300 ° C during the cavity cooldown from 800 ° C and held at 165 ° C , without any degradation in accelerating gradient over the baseline performance. The treatment was applied to several elliptical cavities with frequency ranging from 0.75 to 3.0 GHz, showing an improved quality factor as a result of low temperature nitrogen treatments. The Q rise feature is similar to that achieved by nitrogen alloying Nb cavities at higher temperature, followed by material removal by electropolishing. The surface modification was confirmed by the change in electronic mean free path and tuned with the temperature and duration of heat treatment. The decrease of the temperature-dependent surface resistance with increasing rf field, resulting in a Q rise, becomes stronger with increasing frequency and decreasing temperature. The data suggest a crossover frequency of ∼ 0.95 GHz above that the Q rise phenomenon occurs at 2 K. Some of these results can be explained qualitatively with an existing model of intrinsic field-dependence of the surface resistance with both equilibrium and nonequilibrium quasiparticle distribution functions. The change in the Q slope below 0.95 GHz may result from masking contribution of trapped magnetic flux to the residual surface resistance. Published by the American Physical Society 2024

43 PARTICLE ACCELERATORS↗

DOE OSTI2024

Separate the Role of Southern and Northern Extra‐Tropical Pacific in Tropical Pacific Climate Variability

Abstract Observational and modeling studies have elucidated the influential role played by the southern and northern extratropical Pacific (SEP and NEP) forcing in shaping dynamics of tropical Pacific climate variability. However, the relative importance of the NEP and SEP and the timescale on which they impact the tropics remain unclear. Using a linear inverse model (LIM) that selectively incorporates or excludes tropical‐extratropical coupling, we find a reduction in tropical interannual variability (∼40%) and low‐frequency (sub‐decadal to decadal) variability in the southeastern tropical Pacific region (∼70%) in the absence of SEP. Conversely, the absence of NEP yields no significant impact on tropical interannual variability but markedly diminishes low‐frequency variability in the central tropical Pacific region (∼70%). LIM and statistic diagnostics on CMIP6 models show the low‐frequency to total variability ratio in the tropical Pacific depending on their NEP and SEP representation. Models with more (less) low‐frequency power tend to show stronger NEP (SEP) dynamics.

Geology↗

DOE OSTI2020

Face Recognition Oak Ridge (FaRO): A Framework for Distributed and Scalable Biometrics Applications

The facial biometrics community has seen a recent abundance of high-accuracy facial analytic models become freely available. Although these models' capabilities in facial detection, landmark detection, attribute analysis, and recognition are ever-increasing, they aren't always straightforward to deploy in a real-world environment. In reality, the use of the field's ever growing collection of models is becoming exceedingly difficult as library dependencies update and deprecate. Researchers often encounter headaches when attempting to utilize multiple models requiring different or conflicting software packages. Face Recognition Oak Ridge (FaRO) is an open-source project designed to provide a highly modular, flexible framework for unifying facial analytic models through a compartmentalized plug-and-play paradigm built on top of the gRPC (Google Remote Procedure Call) protocol. FaRO's server-client architecture and flexible portability allows easy construction of modularized and heterogeneous face analysis pipelines, distributed over many machines with differing hardware and software resources. This paper outlines FaRO's architecture and current capabilities, along with some experiments in model testing and distributed scaling through FaRO.

Bolme, David↗

DOE OSTI2022

Impact of carbonation on leaching of constituents from a cementitious waste form for treatment of low activity waste at the DOE Hanford site

Carbonation can be a major aging process during disposal of alkaline cementitious waste forms and can impact constituent leaching by changes in material alkalinity, pore structure, and controlling mineral phases. The effect of carbonation on the leaching of major and trace constituents from Cast Stone, a cementitious waste form developed to treat high salt content low activity waste, was studied through a combination of leaching experiments and reactive transport simulations. Diffusive transport of constituents in the waste form was evaluated using reactive transport modeling of diffusion-controlled leaching test results and a geochemical speciation model derived from pH-dependent leaching. Comparisons between Cast Stone materials aged under nitrogen, air, and 2% carbon dioxide in nitrogen showed that carbonation impacts solubility, physical retention and observed diffusivity of major and trace constituents. Carbonation under 2% CO 2 decreased the diffusion-controlled leaching of chromium by two orders of magnitude. Finally, modeling results suggest that carbonation may also decrease solubility of technetium while changes to microstructure by carbonation increases effective diffusivity of constituents in Cast Stone.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2023

A hybrid 3D/2D field response calculation for liquid argon detectors with PCB based anode plane

Liquid Argon Time Projection Chamber (LArTPC) technology is commonly utilized in neutrino detector designs. It enables detailed reconstruction of neutrino events with high spatial precision and low energy threshold. Its field response (FR) model describes the time-dependent electric currents induced in the anode-plane electrodes when ionization electrons drift nearby. An accurate and precise FR is a crucial input to LArTPC detector simulations and charge reconstruction. Established LArTPC designs have been based on parallel wire planes. It allows accurate and computationally economic two-dimensional (2D) FR models utilizing the translational symmetry along the direction of the wires. Recently, novel LArTPC designs utilize electrodes formed on printed circuit board (PCB) in the shape of strips with through holes. The translational symmetry is no longer a good approximation near the electrodes and a new FR calculation that employs regions with three dimensions (3D) has been developed. Extending the 2D models to 3D would be computationally expensive. Fortuitously, the nature of strips with through holes allows for a computationally economic approach based on the finite-difference method (FDM). In this paper, we present a new software package pochoir that calculates LArTPC field response for these new strip-based anode designs. This package combines 3D calculations in the volume near the electrodes with 2D far-field solutions to achieve fast and precise field response computation. We apply the resulting FR to simulate and reconstruct samples of cosmic-ray muons and 39 Ar decays from a Vertical Drift (VD) detector prototype operated at CERN. We find the difference between real and simulated data within 5%. Current state-of-the-art LArTPC software requires a 2D FR which we provide by averaging over one dimension and estimate that variations lost in this average are smaller than 7%.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

Reconstructing f ( T ) gravity and exploring the torsion driven warm inflationary cosmology

The current paper reports an investigation of a warm inflationary scenario in the context of f(T) gravity for a spatially flat FLRW universe. In our model, inflation is driven purely by the torsional sector of f(T) gravity, without introducing any additional scalar fields. We focus on the high dissipative regime (R >> 1), reconstruct the Hubble parameter as a function of the e-folding number N, and derive the slow-roll parameters ε 1 (N) and ε 2 (N). The study has encapsulated the dynamics of inflation and its duration under strong dissipation. The dissipative coefficient Γ is modeled with a temperature-dependent power-law form, linking the inflationary dynamics to thermal corrections and the particle content of the early universe. The analysis has affirmed that the torsion-induced energy density ρ T successfully transitions to radiation energy density ρ rad , facilitating a graceful exit from inflation. Finally, we have validated our model by comparing the scalar spectral index and tensor-to-scalar ratio with Planck 2018 results, demonstrating consistency within observational bounds. Additionally, it is verified that the thermal domination condition T * /H > 1 and the torsion dominance condition ρ T /ρ rad > 1 are satisfied.

Ghosh, Moli [Amity University, Kolkata (India); Mr↗

DOE OSTI2020

Simulations of activities, solubilities, transport properties, and nucleation rates for aqueous electrolyte solutions

This article reviews recent molecular simulation studies of "collective" properties of aqueous electrolyte solutions, specifically free energies and activity coefficients, solubilities, nucleation rates of crystals, and transport coefficients. These are important fundamental properties for biology and geoscience, but also relevant for many technological applications. Their determination from molecular-scale calculations requires large systems and long sampling times, as well as specialized sampling algorithms. As a result, such properties have not typically been taken into account during optimization of force field parameters; thus, they provide stringent tests for the transferability and range of applicability of proposed molecular models. There has been significant progress on simulation algorithms to enable the determination of these properties with good statistical uncertainties. Comparisons of simulation results to experimental data reveal deficiencies shared by many commonly used models. Moreover, there appear to exist specific tradeoffs within existing modeling frameworks, so that good prediction of some properties is linked to poor prediction for specific other properties. For example, non-polarizable models that utilize full charges on the ions generally fail to predict accurately both activity coefficients and solubilities; the concentration dependence of viscosity and diffusivity for these models is also incorrect. Scaled-charge models improve the dynamic properties and could also perform well for solubilities, but fail in the prediction of nucleation rates. Even models that do well at room temperature for some properties generally fail to capture their experimentally observed temperature dependence. Finally, the main conclusion from the present review is that qualitatively new physics will need to be incorporated in future models of electrolyte solutions to allow description of collective properties for broad ranges of concentrations, temperatures, and solvent conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Testing of an Optical Fiber--Based Gamma Thermometer in the High Flux Isotope Reactor Gamma Irradiation Facility

This report describes the design, thermal modeling, and gamma irradiation testing of an optical fiber–based gamma thermometer (OFBGT), which was irradiated in the High Flux Isotope Reactor (HFIR) Gamma Irradiation Facility (GIF). OFBGTs are a promising technology for application in nuclear reactors because they can provide a distributed measurement of gamma ray heating rate, unlike thermocouple-based gamma thermometers, which are fixed in-core sensors that can be used in boiling water reactors to calibrate local power range monitors. OFBGTs measure gamma ray heating rate by measuring the temperature difference between a pair of optical fibers; one fiber is in thermal contact with a heat sink (usually the reactor coolant), and the other is in thermal contact with a thermally isolated mass. The device can be calibrated with a heating wire within the thermal mass. The OFBGT that was designed and fabricated at Oak Ridge National Laboratory can measure distributed gamma ray heating rate over an effective measurement length of 61 cm, and the outer diameter of the sensor is 12.7 mm, giving the prototypical sensor design a relatively small footprint. The sensor housing is backfilled with Ar to ensure a well-predicted thermal response that is not affected by humidity or chemical interactions during operation. For calibration, the sensor design uses a Ni–Cr wire, which can be supplied with currents from 0 to 1 A to capture the wide range of potential gamma ray heating rates expected in HFIR’s spent fuel elements. The OFBGT was thermally modeled analytically and numerically; both models account for temperature-dependent thermal conductivities of the materials and show good agreement. The thermal response of the sensor inside spent HFIR fuel elements was simulated for times up to 1 year after discharge of the fuel element. Out-of-pile open-air tests indicated that the steady-state response of the sensor matches modeled results within experimental uncertainty. Calibration tests were performed using electrical heating in the HFIR spent fuel pool, above the fuel elements, to establish a relationship between the difference in spectral shift measured by optical fibers located inside and outside the OFBGT and the applied electrical heating. Subsequently, the OFBGT was placed within the the spent fuel element from HFIR cycle 501 to measure the spatial profile of the gamma heating rates. Results showed good agreement between the theoretical and measured gamma dose rate profiles, with maximum deviations of ~10% or less.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2022

Data-driven wind turbine wake modeling via probabilistic machine learning

Wind farm design primarily depends on the variability of the wind turbine wake flows to the atmospheric wind conditions and the interaction between wakes. Physics-based models that capture the wake flow field with high-fidelity are computationally very expensive to perform layout optimization of wind farms, and, thus, data-driven reduced-order models can represent an efficient alternative for simulating wind farms. In this work, we use real-world light detection and ranging (LiDAR) measurements of wind-turbine wakes to construct predictive surrogate models using machine learning. Specifically, we first demonstrate the use of deep autoencoders to find a low-dimensional latent space that gives a computationally tractable approximation of the wake LiDAR measurements. Then, we learn the mapping between the parameter space and the (latent space) wake flow fields using a deep neural network. Additionally, we also demonstrate the use of a probabilistic machine learning technique, namely, Gaussian process modeling, to learn the parameter-space-latent-space mapping in addition to the epistemic and aleatoric uncertainty in the data. Finally, to cope with training large datasets, we demonstrate the use of variational Gaussian process models that provide a tractable alternative to the conventional Gaussian process models for large datasets. Furthermore, we introduce the use of active learning to adaptively build and improve a conventional Gaussian process model predictive capability. Overall, we find that our approach provides accurate approximations of the wind-turbine wake flow field that can be queried at an orders-of-magnitude cheaper cost than those generated with high-fidelity physics-based simulations.

Deep neural networks↗

DOE OSTI2020

Windowed least-squares model reduction for dynamical systems

Here we propose a windowed least-squares (WLS) approach for model reduction of dynamical systems. The proposed approach sequentially minimizes the time-continuous full-order-model residual within a low-dimensional space–time trial subspace over time windows. The approach comprises a generalization of existing model reduction approaches, as particular instances of the methodology recover Galerkin, least-squares Petrov–Galerkin (LSPG), and space–time LSPG projection. In addition, the approach addresses key deficiencies in existing model reduction techniques, e.g., the dependence of LSPG and space–time LSPG projection on the time discretization and the exponential growth in time exhibited by a posteriori error bounds for both Galerkin and LSPG projection. We consider two types of space–time trial subspaces within the proposed approach: one that reduces only the spatial dimension of the full-order model, and one that reduces both the spatial and temporal dimensions of the full-order model. For each type of trial subspace, we consider two different solution techniques: direct (i.e., discretize then optimize) and indirect (i.e., optimize then discretize). Numerical experiments conducted using trial subspaces characterized by spatial dimension reduction demonstrate that the WLS approach can yield more accurate solutions with lower space–time residuals than Galerkin and LSPG projection.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Gravitational waves from current-carrying cosmic strings

Cosmic strings are predicted by many Standard Model extensions involving the cosmological breaking of a symmetry with nontrivial first homotopy group and represent a potential source of primordial gravitational waves (GWs). Present efforts to model the GW signal from cosmic strings are often based on minimal models, such as, e.g., the Nambu-Goto action that describes cosmic strings as exactly one-dimensional objects without any internal structure. In order to arrive at more realistic predictions, it is therefore necessary to consider nonminimal models that make an attempt at accounting for the microscopic properties of cosmic strings. With this goal in mind, we derive in this paper the GW spectrum emitted by current-carrying cosmic strings (CCCSs), which may form in a variety of cosmological scenarios. Our analysis is based on a generalized version of the velocity-dependent one-scale (VOS) model, which, in addition to the mean velocity and correlation length of the string network, also describes the evolution of a chiral (light-like) current. Here we are able to show, the solutions of the VOS equations imply a temporarily growing fractional cosmic-string energy density, Ω cs . This results in an enhanced GW signal across a broad frequency interval, whose boundaries are determined by the times of generation and decay of cosmic-string currents. Our findings have important implications for GW experiments in the Hz to MHz band and motivate the construction of realistic particle physics models that give rise to large currents on cosmic strings.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Sparsity-Independent Lyapunov Exponent in the Sachdev-Ye-Kitaev Model

The saturation of a recently proposed universal bound on the Lyapunov exponent has been conjectured to signal the existence of a gravity dual. This saturation occurs in the low-temperature limit of the dense Sachdev-Ye-Kitaev (SYK) model, N Majorana fermions with q body ( q > 2 ) infinite-range interactions. We calculate certain out-of-time-order correlators (OTOCs) for N ≤ 64 fermions for a highly sparse SYK model and find no significant dependence of the Lyapunov exponent on sparsity up to near the percolation limit where the Hamiltonian breaks up into blocks. This provides strong support to the saturation of the Lyapunov exponent in the low-temperature limit of the sparse SYK. A key ingredient to reaching N = 64 is the development of a novel quantum spin model simulation library that implements highly optimized matrix-free Krylov subspace methods on graphical processing units. This leads to a significantly lower simulation time as well as vastly reduced memory usage over previous approaches, while using modest computational resources. Strong sparsity-driven statistical fluctuations require both the use of a much larger number of disorder realizations with respect to the dense limit and a careful finite size scaling analysis. The saturation of the bound in the sparse SYK points to the existence of a gravity analog that would enlarge substantially the number of field theories with this feature. Published by the American Physical Society 2024

Physics↗

DOE OSTI2021

METHODOLOGY AND APPLICATION OF PHYSICAL SECURITY EFFECTIVENESS BASED ON DYNAMIC FORCE-ON-FORCE MODELING

This paper describes ongoing work within the Light Water Reactor Sustainability (LWRS) Program at Idaho National Laboratory (INL) to optimize security and cost of nuclear power plants (NPPs). It reviews the conservatisms in conventional physical security posture and regulations. It introduces the dynamic risk assessment tool developed at INL, Event Modeling Risk Assessment using Linked Diagrams (EMRALD). The dynamic assessment methodology leverages EMRALD to process results of force-on-force (FOF) simulations and crediting safety mitigation actions from probabilistic risk assessment (PRA) models as well as diverse and flexible coping strategies (FLEX) mitigation strategies. Timing information from these simulations are compared against the available time to perform mitigations obtained from Reactor Excursion and Leak Analysis Program (RELAP5) simulations. To illustrate the methodology, a station blackout (SBO) attack scenario was modeled in commercially available FOF simulation tools. The simulation results provide valuable insights into possible attack outcomes and as the probabilistic risk of a core damage event given these outcomes. Safety mitigation procedures were modeled in EMRALD, and were dependent on the attack outcomes by considering human operator uncertainties. RELAP5 simulations incorporating human and hardware uncertainties were performed to estimate the distribution of time-to-core damage. The results demonstrate that, even in the extreme case of a successful adversarial attack, plant mitigation strategies provide significantly high-likelihood of preventing radiological release. The proposed modeling and simulation framework of integrating FLEX equipment with FOF models enables the NPPs to credit FLEX portable equipment in the plant security posture, resulting in an efficient and optimized physical security.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2025

Development of a thermal creep model for aluminum alloy 6061 cladding in U-10Mo monolithic fuel plates

Plate-type fuel elements consisting of a high-density, low-enriched uranium (LEU) U–10Mo-based fuel foil encapsulated in an aluminum alloy (AA) cladding are fabricated using the hot isostatic pressing (HIP) technique. During the HIP process, the fuel plate system is heated to 560 °C, then cooled to room temperature. This heat cycle significantly affects the mechanical properties of the aluminum cladding, and experimental investigations have shown that, post-HIP bonding, the mechanical properties of the aluminum cladding transition from those of AA 6061-T6 to something closer to the O temper. More specifically, the ultimate strength of the cladding decreases while its ductility increases, making it challenging to capture the changes in mechanical behavior and material properties. Understanding the residual stresses generated during the HIP process is critical for assessing the fuel plate’s integrity under various temperature, pressure, and irradiation. To simulate the HIP bonding process, the elastic, plastic, and thermal properties of the cladding are assumed to be similar to those of AA 6061-O temper. However, the primary challenge lies in the lack of available data for the creep model of the AA 6061 cladding during this transient process of HIP. The present study focuses on developing a computational model that predicts the creep behavior of the aluminum cladding in the fuel plates during the HIP process, as cladding creep significantly influences the residual stresses generated in U-10Mo fuel plates during HIP fabrication. Furthermore, as HIP bonding occurs at high temperatures that are nearing the melting point of aluminum, the present work considered a temperature-dependent Arrhenius-type creep model. In particular, a hyperbolic sine creep model is employed to estimate the creep properties of the as-fabricated aluminum cladding. In conclusion, the residual stresses predicted in the U-10Mo fuel when using the newly calibrated creep model closely align with the experimental measurements, validating the model’s accuracy.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2022

APPLICATION OF OBJECTIVES-DRIVEN ASSURANCE CASES TO SYSTEM DEVELOPMENT IN AN EVOLVING ACQUISITION MODEL

System properties such as “safety” and “dependability” cannot, in practice, be proven, and must be argued in an “assurance case” aimed at supporting risk-acceptance decisions that have to be made by system acquirers and/or regulatory authorities. The paper is concerned with applications of the “assurance case” idea early in design and development of new systems, when (apart from dedicated testing) the only available operating experience information derives from previous (non-identical) systems. Much of the discussion is based on an evolving acquisition model at the US National Aeronautics and Space Administration; previously, most major systems were developed in-house, but some major systems will now be developed by and acquired from commercial providers. Key points discussed include the following. (1) By promoting a particular kind of focused discussion between acquirers and providers, the use of assurance cases should be particularly valuable under the new acquisition model. (2) In principle, objectives-driven (sometimes called “performance-based”) approaches to assurance of performance have significant advantages in cases where they are applicable. (3) For truly novel systems, completeness of the safety analysis is a significant issue; it is important for the assurance case to include a commitment by the provider (or applicant) to seriously pursue analysis of operating experience, so that previously unrecognized hazards can be identified and addressed. (4) Inquiries into major accidents often point to deficiencies in management oversight in all parts of the life cycle; management processes need to be addressed in the formulation and the implementation of an assurance case. Under the new acquisition model, these considerations imply a serious reconsideration of the way in which the development process is managed by both providers and acquirers.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2022

Application of Objectives-Driven Assurance Cases to System Development in an Evolving Acquisition Model

99 GENERAL AND MISCELLANEOUS↗