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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.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Mixing Cell Model: A One-Dimensional Numerical Model for Assessment of Water Flow and Contaminant Transport in the Unsaturated Zone

This report describes the Mixing Cell Model code, a one dimensional model for water flow and solute transport in the unsaturated zone under steady state or transient flow conditions. The model is based on the principles and assumptions underlying mixing-cell model formulations. The unsaturated zone is discretized into a series of independent mixing cells. Each cell may have unique hydrologic, lithologic, and sorptive properties. Ordinary differential equations describe the material (water and solute) balance within each cell. Water-flow equations are derived from the continuity equation, assuming that unit gradient conditions exist at all times in each cell. Pressure gradients are considered implicitly through model discretization. Unsaturated hydraulic conductivity and moisture contents are determined by the material specific moisture-characteristic curves. Solute-transport processes include explicit treatment of advective processes, first order chain decay, and linear sorption reactions. Dispersion is addressed through implicit and explicit dispersion. Implicit dispersion is an inherent feature of all mixing-cell models and originates from the formulation of the problem in terms of mass balance around fully mixed volume elements. Expressions are provided that relate implicit dispersion to the physical dispersion of the system. Two FORTRAN codes were developed to solve the water flow and solute-transport equations: (1) the Mixing Cell Model for Flow (MCMF) solves transient water-flow problems and (2) the Mixing Cell Model for Transport (MCMT) solves the solute-transport problem. The transient water-flow problem is typically solved first by estimating the water flux through each cell in the model domain as a function of time using the MCMF code. These data are stored in either ASCII or binary files that are later read by the solute transport code (MCMT). Code output includes solute pore water concentrations, water and solute inventories in each cell and at each specified output time, and water and solute fluxes through each cell and specified output time. Computer run times for coupled transient water flow and solute transport were typically several seconds on a 2 GHz Intel Pentium IV desktop computer. The model was benchmarked against analytical solutions and finite element approximations to the partial differential equations (PDE) describing unsaturated flow and transport. Differences between the maximum solute flux estimated by the mixing cell model and the PDE models were typically less than two percent. This revision includes an option for a fixed concentration lower boundary condition for diffusive fluxes for versions 020321 and later.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Photoproduction of Lambda* Resonances using the CLAS Detector

This thesis presents the study of the reaction yp -> K^+Lambda* using the photo production data from the CLAS-g12 experiment performed in Hall B of Jefferson Laboratory. The decay of Lambda* resonances, Lambda(1520), Lambda(1670), and Lambda(1690), into two exclusive channels, Sigma+pi?and Sigma-pi+, is studied from the detected K+,pi+, and pi?particles. This work aims at understanding photoproduction mechanism to excited state baryons, and to facilitate phenomenological model predictions using precision experimental measurements. A good agreement is established for the Lambda(1520) differential cross sections with the previous CLAS measurements. The differential cross sections as a function of CM angle are extended to higher photon energies. Newly added are the differential cross sections as a function of invariant 4-momentum transfer, which is the natural variable to use for a theoretical model based on a Regge-exchange reaction mechanism. No new N* resonances decaying into the K+Lambda(1520) final state are found. The higher mass resonances, Lambda(1670)1/2- and Lambda(1690)3/2-, are studied for the first time using photoproduction. This work provides a model dependent preliminary cross sections for these excited states.

Shrestha, Utsav↗
DOE OSTI2021

A coupled discontinuous Galerkin-Finite Volume framework for solving gas dynamics over embedded geometries

Herein, we present a computational framework for solving the equations of inviscid gas dynamics using structured grids with embedded geometries. The novelty of the proposed approach is the use of high-order discontinuous Galerkin (dG) schemes and a shock-capturing Finite Volume (FV) scheme coupled via an hp adaptive mesh refinement (hp-AMR) strategy that offers high-order accurate resolution of the embedded geometries. The hp-AMR strategy is based on a multi-level block-structured domain partition in which each level is represented by block-structured Cartesian grids and the embedded geometry is represented implicitly by a level set function. The intersection of the embedded geometry with the grids produces the implicitly-defined mesh that consists of a collection of regular rectangular cells plus a relatively small number of irregular curved elements in the vicinity of the embedded boundaries. High-order quadrature rules for implicitly-defined domains enable high-order accuracy resolution of the curved elements with a cell-merging strategy to address the small-cell problem. The hp-AMR algorithm treats the system with a second-order finite volume scheme at the finest level to dynamically track the evolution of solution discontinuities while using dG schemes at coarser levels to provide high-order accuracy in smooth regions of the flow. On the dG levels, the methodology supports different orders of basis functions on different levels. The space-discretized governing equations are then advanced explicitly in time using high-order Runge-Kutta algorithms. Numerical tests are presented for two-dimensional and three-dimensional problems involving an ideal gas. The results are compared with both analytical solutions and experimental observations and demonstrate that the framework provides high-order accuracy for smooth flows and accurately captures solution discontinuities.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Enhanced Component Performance Study: Emergency Diesel Generators 1998–2018

This report presents an enhanced performance evaluation of emergency diesel generators (EDGs) at U.S. commercial nuclear power plants. This report evaluates component performance over time using (1) Institute of Nuclear Power Operations (INPO) Consolidated Events Database (ICES) data from 1998 through 2018 and (2) maintenance unavailability (UA) performance data from Mitigating Systems Performance Index (MSPI) Basis Document data from 2002 through 2018. The objective is to show estimates of current failure probabilities and rates related to EDGs, trend these data on an annual basis, determine if the current data are consistent with the probability distributions currently recommended for use in NRC probabilistic risk assessments, show how the reliability data differ for different EDG manufacturers and for EDGs with different ratings; and summarize the subcomponents, causes, detection methods, and recovery associated with each EDG failure mode. Engineering analyses were performed with respect to time period and failure mode without regard to the actual number of EDGs at each plant. The factors analyzed are: sub-component, failure cause, detection method, recovery, manufacturer, and EDG rating. A statistically significant increasing trend was identified in the frequency of FTLR demands for emergency power system (EPS) and high pressure core spray (HPCS) EDGs and a statistically significant decreasing trend was identified in the frequency of run > 1H hours for EPS and HPCS EDGs.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

A remote sensing algorithm for vertically resolved cloud condensation nuclei number concentrations from airborne and spaceborne lidar observations

Cloud condensation nuclei (CCN) are mediators of aerosol–cloud interactions (ACIs), contributing to the largest uncertainties in the understandings of global climate change. We present a novel remote-sensing-based algorithm that quantifies the vertically resolved CCN number concentrations (N CCN ) using aerosol optical properties measured by a multiwavelength lidar. The algorithm considers five distinct aerosol subtypes with bimodal size distributions. The inversion used the lookup tables developed in this study, based on the observations from the Aerosol Robotic Network, to efficiently retrieve optimal particle size distributions from lidar measurements. The method derives dry aerosol optical properties by implementing hygroscopic enhancement factors in lidar measurements. The retrieved optically equivalent particle size distributions and aerosol-type-dependent particle composition are utilized to calculate critical diameters using κ-Köhler theory and N CCN at six supersaturations ranging from 0.07 % to 1.0 %. Sensitivity analyses indicate that uncertainties in extinction coefficients and relative humidity greatly influence the retrieval error in N CCN . The potential of this algorithm is further evaluated by retrieving N CCN using airborne lidar from the NASA ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES) campaign and is validated against simultaneous measurements from the CCN counter. The independent validation with robust correlation demonstrates promising results. Furthermore, the N CCN has been retrieved for the first time using a proposed algorithm from spaceborne lidar – Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) – measurements. The application of this new capability demonstrates the potential for constructing a 3D CCN climatology at a global scale, which helps to better quantify ACI effects and thus reduce the uncertainty in aerosol climate forcing.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Unveiling the Potential of MeshGraphNets for Predicting Subsurface Evolution in Carbon Storage Projects

This is the conference paper accompanying an oral presentation “Unveiling the Potential of MeshGraphNets for Predicting Subsurface Evolution in Carbon Storage Projects” at the 17th International Conference on Greenhouse Gas Control Technologies GHGT-17 held in Calgary, Canada, October 20-24 , 2024. Carbon capture and storage (CCS) technology is critical for mitigating climate change but requires effective subsurface reservoir management to ensure safe containment of injected CO2. Accurate predictions of reservoir pressure and saturation are essential for assessing long-term CCS performance. Traditional numerical simulations, while effective, are computationally intensive, time-consuming, and constrained by data discretization. Previous work has shown the effectiveness of MeshGraphNets (MGN), a graph-based machine learning framework, as an innovative alternative for predicting reservoir behavior. MGN leverages graph neural networks (GNNs) and mesh representations to model complex geological formations, offering superior adaptability across different discretizations and reservoir configurations. Classic MGN implementations utilize an autoregressive technique to predict future behavior based on current predictions, but this technique is hampered by error accumulation over time. To enhance the model accuracy in time-series predictions, this study implemented a multi-step rollout strategy that integrates autoregressive predictions during training to stabilize prediction of saturation over time. Using the Illinois Basin – Decatur Project (IBDP) dataset, comprising 100 simulations of CO2 injection, pressure, and saturation changes, the framework demonstrated its ability to learn spatial dependencies and temporal dynamics. With inputs including permeabilities, porosities, and injection rates, MGN accurately predicted CO2 plume evolution over time, even with limited training data. Moreover, the addition of a multi-step rollout procedure during training improved the ability of MGN to predict stably over time by ~15%. This research positions MGN, enhanced with multi-step rollout capabilities, as a robust and efficient tool for CCS applications. It advances the field by enabling precise, computationally efficient predictions of reservoir behavior, providing a foundation for the broader adoption of machine learning frameworks in CCS and other geoscience domains.

Holcomb, Paul↗
DOE OSTI2024

BioRT‐HBV 1.0: A Biogeochemical Reactive Transport Model at the Watershed Scale

Abstract Reactive Transport Models (RTMs) are essential tools for understanding and predicting intertwined ecohydrological and biogeochemical processes on land and in rivers. While traditional RTMs have focused primarily on subsurface processes, recent watershed‐scale RTMs have integrated ecohydrological and biogeochemical interactions between surface and subsurface. These emergent, watershed‐scale RTMs are often spatially explicit and require extensive data, computational power, and computational expertise. There is however a pressing need to create parsimonious models that require minimal data and are accessible to scientists with limited computational background. To that end, we have developed BioRT‐HBV 1.0, a watershed‐scale, hydro‐biogeochemical RTM that builds upon the widely used, bucket‐type HBV model known for its simplicity and minimal data requirements. BioRT‐HBV uses the conceptual structure and hydrology output of HBV to simulate processes including advective solute transport and biogeochemical reactions that depend on reaction thermodynamics and kinetics. These reactions include, for example, chemical weathering, soil respiration, and nutrient transformation. The model uses time series of weather (air temperature, precipitation, and potential evapotranspiration) and initial biogeochemical conditions of subsurface water, soils, and rocks as input, and output times series of reaction rates and solute concentrations in subsurface waters and rivers. This paper presents the model structure and governing equations and demonstrates its utility with examples simulating carbon and nitrogen processes in a headwater catchment. As shown in the examples, BioRT‐HBV can be used to illuminate the dynamics of biogeochemical reactions in the invisible, arduous‐to‐measure subsurface, and their influence on the observed stream or river chemistry and solute export. With its parsimonious structure and easy‐to‐use graphical user interface, BioRT‐HBV can be a useful research tool for users without in‐depth computational training. It can additionally serve as an educational tool that promotes pollination of ideas across disciplines and foster a diverse, equal, and inclusive user community.

Sadayappan, Kayalvizhi↗
DOE OSTI2021

First results of the CAST-RADES haloscope search for axions at 34.67 μ eV

We present results of the Relic Axion Dark-Matter Exploratory Setup (RADES), a detector which is part of the CERN Axion Solar Telescope (CAST), searching for axion dark matter in the 34.67 μeV mass range. A radio frequency cavity consisting of 5 sub-cavities coupled by inductive irises took physics data inside the CAST dipole magnet for the first time using this filter-like haloscope geometry. An exclusion limit with a 95% credibility level on the axion-photon coupling constant of g aγ ≳ 4 × 10 -13 GeV -1 over a mass range of 34.6738 μeV < m a < 34.6771 μeV is set. This constitutes a significant improvement over the current strongest limit set by CAST at this mass and is at the same time one of the most sensitive direct searches for an axion dark matter candidate above the mass of 25 μeV. The results also demonstrate the feasibility of exploring a wider mass range around the value probed by CAST-RADES in this work using similar coherent resonant cavities.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Practices for Demonstrating Energy Savings from Commercial PACE Projects

Nearly three-fourths of U.S. states have authorized local governments to use voluntary special assessments on commercial properties to finance energy improvements that boost economic development, create jobs, increase property values and advance energy goals. Commercial Property Assessed Clean Energy (C-PACE) financing allows building owners to repay the borrowed capital — from private or public sources — over time using their property as security. Berkeley Lab is supporting the Department of Energy’s Commercial PACE Working Group by developing a series of C-PACE issue briefs. The second brief in this series, Practices for Demonstrating Energy Savings from Commercial PACE Projects, looks at common practices for demonstrating energy savings to support state and local governments that sponsor C-PACE programs and want to track their energy impacts. This brief reviews: -The value proposition and trade-offs of conducting energy impact assessments for C-PACE programs; -Methods to quantify energy savings impacts from energy efficiency building improvements; and -Available resources and tools to support energy impact assessments. C-PACE programs may benefit from energy impact assessments for many reasons, including: -Validating the public benefits of the programs -Demonstrating that C-PACE can deliver participant benefits -Illustrating program impacts on public policy goals -Generating data to help improve program performance Many C-PACE programs are collecting data on project energy savings impacts, and these data can be leveraged to further support decision making and program implementation. Potential drawbacks to energy impact assessments may include added cost and burdens on property owners (e.g., the need to collect building energy consumption data). Where these burdens are considerable, they might slow program uptake. State and local governments can balance the benefits of energy impact assessments with the range of costs and accuracy inherent to available assessment methodologies. Additionally, depending on the policy context in the state or local government, a C-PACE program may be able to leverage existing efforts (e.g., building energy benchmarking programs) to reduce impact assessment costs, align with building owner practices and expectations, and efficiently assess program impact.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Coherent light control of a metastable hidden state

Metastable phases present a promising route to expand the functionality of complex materials. Of particular interest are light-induced metastable phases that are inaccessible under equilibrium conditions, as they often host new, emergent properties switchable on ultrafast timescales. However, the processes governing the trajectories to such hidden phases remain largely unexplored. Here, using time- and angle-resolved photoemission spectroscopy, we investigate the ultrafast dynamics of the formation of a hidden quantum state in the layered dichalcogenide 1T-TaS 2 upon photoexcitation. Our results reveal the nonthermal character of the transition governed by a collective charge-density-wave excitation. Using a double-pulse excitation of the structural mode, we show vibrational coherent control of the phase-transition efficiency. Our demonstration of exceptional control, switching speed, and stability of the hidden state are key for device applications at the nexus of electronics and photonics.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Characterization of Rare-earth Doped Thermal Barrier Coatings for Phosphor Thermometry

Thermal Barrier Coatings have been extensively used to protect and insulate the metallic components in turbine engines from extreme environments to achieve higher turbine inlet temperatures, resulting in an increase in combined engine cycle efficiency, lowering NOx emissions and fuel consumption. Additionally, as the major failure mechanisms determining lifetime are thermally activated during engine operation, uncertainty in temperature measurements affects lifetime prediction. Early detection of Thermal Barrier Coatings spallation symptoms, associated with local delamination induced temperature changes, can reduce forced engine outages. Further improvements are envisioned with the development of more reliable measurement techniques. For this purpose, Phosphor Thermometry has been considered a promising method for precision monitoring of turbine blade coatings that contain embedded phosphor dopants. In this work, a modified four-flux Kubelka-Munk model for luminescent rare-earth doped Thermal Barrier Coating configurations supported the design and the fabrication of viable sensing coatings for potential industrial implementation. Phosphor Thermometry instrumentation was developed with the objective of expanding capabilities of the technique, using a synchronized acquisition method on sensing coatings. Experiments on an innovative Erbium-Europium co-doped Yttria-Stabilized Zirconia coating have demonstrated the effectiveness of this advanced Phosphor Thermometry instrument with enhanced sensitivity and extended temperature range. Delamination progression monitoring was achieved for the first time using a Thermal Barrier Coating configuration subjected to indentation that includes a thin luminescent layer deposited on the surface and associating the multi-layer configuration with a predictive model that evaluates the advancement of the degradation of the coatings. To further ensure the integrity of the phosphor doped coatings, synchrotron X-ray diffraction was performed to characterize the specific residual strains and thermal expansion of the materials, determining mechanical robustness and compatibility with state-of-the-art Thermal Barrier Coatings. The outcomes of this work pave the way for in-situ temperature measurements on phosphor-doped turbine blade coatings with increased performance and accuracy.

Fouliard, Quentin↗
DOE OSTI2021

Measurements of sensor radiation damage in the ATLAS inner detector using leakage currents

Non-ionizing energy loss causes bulk damage to the silicon sensors of the ATLAS pixel and strip detectors. This damage has important implications for data-taking operations, charged-particle track reconstruction, detector simulations, and physics analysis. This paper presents simulations and measurements of the leakage current in the ATLAS pixel detector and semiconductor tracker as a function of location in the detector and time, using data collected in Run 1 (2010-2012) and Run 2 (2015-2018) of the Large Hadron Collider. The extracted fluence shows a much stronger |z|-dependence in the innermost layers than is seen in simulation. Furthermore, the overall fluence on the second innermost layer is significantly higher than in simulation, with better agreement in layers at higher radii. These measurements are important for validating the simulation models and can be used in part to justify safety factors for future detector designs and interventions.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Probing interspecies metabolic interactions within a synthetic binary microbiome using genome-scale modeling

Metabolic interactions within a microbial community play a key role in determining the structure, function, and composition of the community. However, due to the complexity and intractability of natural microbiomes, limited knowledge is available on interspecies interactions within a community. In this work, using a binary synthetic microbiome, a methanotroph-photoautotroph (M-P) coculture, as the model system, we examined different genome-scale metabolic modeling (GEM) approaches to gain a better understanding of the metabolic interactions within the coculture, how they contribute to the enhanced growth observed in the coculture, and how they evolve over time. Using batch growth data of the model M-P coculture, we compared three GEM approaches for microbial communities. Two of the methods are existing approaches: SteadyCom, a steady state GEM, and dynamic flux balance analysis (DFBA) Lab, a dynamic GEM. We also proposed an improved dynamic GEM approach, DynamiCom, for the M-P coculture. SteadyCom can predict the metabolic interactions within the coculture but not their dynamic evolutions; DFBA Lab can predict the dynamics of the coculture but cannot identify interspecies interactions. DynamiCom was able to identify the cross-fed metabolite within the coculture, as well as predict the evolution of the interspecies interactions over time. A new dynamic GEM approach, DynamiCom, was developed for a model M-P coculture. Constrained by the predictions from a validated kinetic model, DynamiCom consistently predicted the top metabolites being exchanged in the M-P coculture, as well as the establishment of the mutualistic N-exchange between the methanotroph and cyanobacteria. The interspecies interactions and their dynamic evolution predicted by DynamiCom are supported by ample evidence in the literature on methanotroph, cyanobacteria, and other cyanobacteria-heterotroph cocultures.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Exact-Factorization-Based Surface Hopping for Multistate Dynamics

A surface-hopping algorithm recently derived from the exact factorization approach, SHXF, introduces an additional term in the electronic equation of surface hopping that couples electronic states through the quantum momentum. Furthermore, this term not only provides a first-principles description of decoherence, but here we show it is crucial to accurately capture nonadiabatic dynamics when more than two states are occupied at any given time. Using a vibronic coupling model of the uracil cation, we show that the lack of this term in traditional surface-hopping methods, including those with decoherence corrections, leads to failure to predict the dynamics through a three-state intersection, while SHXF performs similarly to the multiconfiguration time-dependent Hartree quantum dynamics benchmark.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Revealing the Structural Evolution of Green Rust Synthesized in Ionic Liquids by In Situ Molecular Imaging

Abstract Ionic liquids are green solvents that have wide applications in material synthesis, catalysis, and separation. A model switchable ionic liquid (SWIL) consisting of 1,8‐diazabicycloundec‐7‐ene (DBU) and 1‐hexanol with carbon dioxide (CO 2 ) as the trigger gas is chosen to synthesize nanocrystalline green rust. Under anoxic conditions, by adding iron (II) acetate (Fe(C 2 H 3 O 2 ) 2 ) and methanol to the degassed SWIL, a nanoparticulate green rust with carbonate (nano‐GR) is synthesized. More importantly, the molecular structural change of the ionic liquid resulting in green rust crystallines is first characterized using in situ liquid using time‐of‐flight secondary ion mass spectrometry (ToF‐SIMS) coupled with the system for analysis at the liquid vacuum interface (SALVI), a vacuum compatible microfluidic reactor in this work. Dimers and ionic clusters consisting ferric and ferrous ions are identified in liquid ToF‐SIMS spectra. Spectral principal component analysis is used to confirm that these ion pairs including dimers and cluster ions are different from nonionic liquids. The results show that liquid ToF‐SIMS can be a useful tool to study complex liquids at the molecular level providing insights into predicative synthesis of nanomaterials using environmentally friendly green solvents and giving unique visualization of the evolving material interface due to nucleation.

Shen, Yanjie↗
DOE OSTI2020

Parameterizations of Entrainment-Mixing Mechanisms and their Effects on Cloud Droplet Spectral Width Based on Numerical Simulations

Entrainment-mixing mechanisms significantly affect cloud droplet number concentration, radius, and spectral shape. Quantitative examination of entrainment-mixing effects on cloud droplet spectral width is lacking. Here, we examine the effects of entrainment-mixing processes on cloud microphysics by 12,218 different setups, each simulated 10 times using the Explicit Mixing Parcel Model (EMPM) driven by the observational data from the Third Tibetan Plateau Atmospheric Scientific Experiment (TIPEX-III) campaign. Parameterizations of entrainment-mixing mechanisms are developed by relating homogeneous mixing degree to transition scale number that depends on the dissipation rate and droplet evaporation time scale. The correlation between relative dispersion of cloud droplet size distribution and homogeneous mixing degree changes from negative to positive with the decreasing homogeneous mixing degree. The different relationships are closely related to the competition between complete and partial droplet evaporation and the number concentration of small droplets, which are quantitatively described by two newly introduced dimensionless numbers. The competition is significantly affected by relative humidity and mixing fraction of entrained air as well as turbulence dissipation rate, but not much by cloud droplet number concentration. Especially, when relative humidity and dissipation rate are high, there is only a negative correlation. This study sheds new light on generalizing the homogeneous/inhomogeneous concept by considering relative dispersion, and also provides parameterizations of entrainment-mixing processes and relative dispersion for atmospheric models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Intruder configurations in 29 Ne at the transition into the island of inversion: Detailed structure study of 28 Ne

Detailed γ-ray spectroscopy of the exotic neon isotope 28 Ne has been performed for the first time using the one-neutron removal reaction from 29 Ne on a liquid hydrogen target at 240 MeV/nucleon. Based on an analysis of parallel momentum distributions, a level scheme with spin-parity assignments has been constructed for 28 Ne and the negative-parity states are identified for the first time. The measured partial cross sections and momentum distributions reveal a significant intruder p-wave strength providing evidence of the breakdown of the N=20 and N=28 shell gaps. Only a weak, possible f-wave strength was observed to bound final states. Large-scale shell-model calculations with different effective interactions do not reproduce the large p-wave and small f-wave strength observed experimentally, indicating an ongoing challenge for a complete theoretical description of the transition into the island of inversion along the Ne isotopic chain.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Nuclear decisionmaking, complexity and emerging and disruptive technologies: A comprehensive assessment

The complex interactions of emerging and disruptive technologies (EDTs) could significantly impact nuclear decision-making, particular in an escalating regional conventional conflict. Such conflicts may present governments with a range of nuclear decisions: whether to introduce a nuclear dimension to a crisis, whether to cross the nuclear threshold through limited nuclear use, how to respond to a limited nuclear attack, whether to expand the scope and intensity of initial limited attacks, and whether to escalate to an all-out nuclear war. At each decision point, EDTs create potential risks as well as rewards. EDTs are likely to influence the context for nuclear decision-making and the choices between different courses of action. EDTs could impact the context of nuclear decision-making by improving or degrading situational assessment, the ability to deliberate, and the ability to manage one’s nuclear forces. EDTs could influence the choice between nuclear restraint or escalation by affecting the perceived strategic benefits, escalatory risks, and operational requirements associated with different courses of action. Even though particular combinations of EDTs could precipitate nuclear use in some scenarios, they could encourage restraint in others. The impact and relevance of the same combinations of EDTs might be different at various nuclear decision points. The availability of specific combinations of EDTs at different stages of a conflict would also vary because of the attrition and one-time-use nature of some capabilities. In later stages of a conflict, the decision maker’s confidence in different combinations of EDTs would depend on their previous experience in using them. While the interactions of EDTs are likely to bring additional complexity to a nuclear decision-making process, EDTs are also not the only source of complexity. Broader strategic, military, operational, legal, moral, and emotional factors are also likely to play an important role. These factors may dominate decision-making in a range of potential cases.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗