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At least 163 records · Page 9

An overview of the Western United States Dynamically Downscaled Dataset (WUS-D3)

Abstract. Predicting future climate change over a region of complex terrain, such as the western United States (US), remains challenging due to the low resolution of global climate models (GCMs). Yet the climate extremes of recent years in this region, such as floods, wildfires, and drought, are likely to intensify further as climate warms, underscoring the need for high-quality and high-resolution predictions. Here, we present an ensemble of dynamically downscaled simulations over the western US from 1980–2100 at 9 km grid spacing, driven by 16 latest-generation GCMs. This dataset is titled the Western US Dynamically Downscaled Dataset (WUS-D3). We describe the challenges of producing WUS-D3, including GCM selection and technical issues, and we evaluate the simulations' realism by comparing historical results to temperature and precipitation observations. The future downscaled climate change signals are shaped in physically credible ways by the regional model's more realistic coastlines and topography. (1) The mean warming signals are heavily influenced by more realistic snowpack. (2) Mean precipitation changes are often consistent with wetting on the windward side of mountain complexes, as warmer, moister air masses are uplifted orographically during precipitation events. (3) There are large fractional precipitation increases on the lee side of mountain complexes, leading to potentially significant changes in water resources and ecology in these arid landscapes. (4) Increases in precipitation extremes are generally larger than in the GCMs, driven by locally intensified atmospheric updrafts tied to sharper, more realistic gradients in topography. (5) Changes in temperature extremes are different from what is expected by a shift in mean temperature and are shaped by local atmospheric dynamics and land surface feedbacks. Because of its high resolution, comprehensiveness, and representation of relevant physical processes, this dataset presents a unique opportunity to evaluate societally relevant future changes in western US climate.

Rahimi, Stefan (ORCID:0000000331884462)↗

Modeling personnel turnover in the parametric organization

A model is developed for simulating the dynamics of a newly formed organization, credible during all phases of organizational development. The model development process is broken down into the activities of determining the tasks required for parametric cost analysis (PCA), determining the skills required for each PCA task, determining the skills available in the applicant marketplace, determining the structure of the model, implementing the model, and testing it. The model, parameterized by the likelihood of job function transition, has demonstrated by the capability to represent the transition of personnel across functional boundaries within a parametric organization using a linear dynamical system, and the ability to predict required staffing profiles to meet functional needs at the desired time. The model can be extended by revisions of the state and transition structure to provide refinements in functional definition for the parametric and extended organization.

Dean, Edwin B.↗

Evaluating the Credibility of Transport Processes in Simulations of Ozone Recovery using the Global Modeling Initiative Three-dimensional Model

The Global Modeling Initiative (GMI) has integrated two 36-year simulations of an ozone recovery scenario with an offline chemistry and tra nsport model using two different meteorological inputs. Physically ba sed diagnostics, derived from satellite and aircraft data sets, are d escribed and then used to evaluate the realism of temperature and transport processes in the simulations. Processes evaluated include barri er formation in the subtropics and polar regions, and extratropical w ave-driven transport. Some diagnostics are especially relevant to sim ulation of lower stratospheric ozone, but most are applicable to any stratospheric simulation. The global temperature evaluation, which is relevant to gas phase chemical reactions, showed that both sets of me teorological fields have near climatological values at all latitudes and seasons at 30 hPa and below. Both simulations showed weakness in upper stratospheric wave driving. The simulation using input from a g eneral circulation model (GMI(GCM)) showed a very good residual circulation in the tropics and Northern Hemisphere. The simulation with inp ut from a data assimilation system (GMI(DAS)) performed better in the midlatitudes than it did at high latitudes. Neither simulation forms a realistic barrier at the vortex edge, leading to uncertainty in the fate of ozone-depleted vortex air. Overall, tracer transport in the offline GML(GCM) has greater fidelity throughout the stratosphere tha n it does in the GMI(DAS)

Strahan, Susan E.↗

Probabilistic Modeling of the Renal Stone Formation Module

The Integrated Medical Model (IMM) is a probabilistic tool, used in mission planning decision making and medical systems risk assessments. The IMM project maintains a database of over 80 medical conditions that could occur during a spaceflight, documenting an incidence rate and end case scenarios for each. In some cases, where observational data are insufficient to adequately define the inflight medical risk, the IMM utilizes external probabilistic modules to model and estimate the event likelihoods. One such medical event of interest is an unpassed renal stone. Due to a high salt diet and high concentrations of calcium in the blood (due to bone depletion caused by unloading in the microgravity environment) astronauts are at a considerable elevated risk for developing renal calculi (nephrolithiasis) while in space. Lack of observed incidences of nephrolithiasis has led HRP to initiate the development of the Renal Stone Formation Module (RSFM) to create a probabilistic simulator capable of estimating the likelihood of symptomatic renal stone presentation in astronauts on exploration missions. The model consists of two major parts. The first is the probabilistic component, which utilizes probability distributions to assess the range of urine electrolyte parameters and a multivariate regression to transform estimated crystal density and size distributions to the likelihood of the presentation of nephrolithiasis symptoms. The second is a deterministic physical and chemical model of renal stone growth in the kidney developed by Kassemi et al. The probabilistic component of the renal stone model couples the input probability distributions describing the urine chemistry, astronaut physiology, and system parameters with the physical and chemical outputs and inputs to the deterministic stone growth model. These two parts of the model are necessary to capture the uncertainty in the likelihood estimate. The model will be driven by Monte Carlo simulations, continuously randomly sampling the probability distributions of the electrolyte concentrations and system parameters that are inputs into the deterministic model. The total urine chemistry concentrations are used to determine the urine chemistry activity using the Joint Expert Speciation System (JESS), a biochemistry model. Information used from JESS is then fed into the deterministic growth model. Outputs from JESS and the deterministic model are passed back to the probabilistic model where a multivariate regression is used to assess the likelihood of a stone forming and the likelihood of a stone requiring clinical intervention. The parameters used to determine to quantify these risks include: relative supersaturation (RS) of calcium oxalate, citrate/calcium ratio, crystal number density, total urine volume, pH, magnesium excretion, maximum stone width, and ureteral location. Methods and Validation: The RSFM is designed to perform a Monte Carlo simulation to generate probability distributions of clinically significant renal stones, as well as provide an associated uncertainty in the estimate. Initially, early versions will be used to test integration of the components and assess component validation and verification (V&V), with later versions used to address questions regarding design reference mission scenarios. Once integrated with the deterministic component, the credibility assessment of the integrated model will follow NASA STD 7009 requirements.

kidney stones↗

Global Modeling, Field Campaigns, Upscaling and Ray Desjardins

In the early 1980's, it became apparent that land surface radiation and energy budgets were unrealistically represented in Global Circulation models (GCM's), Shortly thereafter, it became clear that the land carbon budget was also poorly represented in Earth System Models (ESM's), A number of scientific communities, including GCM/ESM modelers, micrometeorologists, satellite data specialists and plant physiologists, came together to design field experiments that could be used to develop and validate the contemporary prototype land surface models. These experiments were designed to measure land surface fluxes of radiation, heat, water vapor and CO2 using a network of flux towers and other plot-scale techniques, coincident with satellite measurements of related state variables, The interdisciplinary teams involved in these experiments quickly became aware of the scale gap between plot-scale measurements (approx 10 - 100m), satellite measurements (100m - 10 km), and GCM grid areas (l0 - 200km). At the time, there was no established flux measurement capability to bridge these scale gaps. Then, a Canadian science learn led by Ray Desjardins started to actively participate in the design and execution of the experiments, with airborne eddy correlation providing the radically innovative bridge across the scale gaps, In a succession of brilliantly executed field campaigns followed up by convincing scientific analyses, they demonstrated that airborne eddy correlation allied with satellite data was the most powerful upscaling tool available to the community, The rest is history: the realism and credibility of weather and climate models has been enormously improved enormously over the last 25 years with immense benefits to the public and policymakers.

Sellers, P. J.↗

Oriented Connectivity-Based Method for Segmenting Solar Loops

A method based on oriented connectivity that can automatically segnient arc-like structures (solar loops) from intensity images of the Sun's corona is introduced. The method is a constructive approach that uses model-guided processing to enable extraction of credible loop structures. Since the solar loops are vestiges of the solar magnetic field, the model-guided processing exploits external estimates of this field s local orientations that are derived from a physical magnetic field model. Empirical studies of the method s effectiveness are also presented. The Oriented Connectivity- Based Method is the first automatic method for the segmentation of solar loops.

Lee, J. K.↗

Wind Field and Trajectory Models for Tornado-Propelled Objects

A mathematical model to predict the trajectory of tornado born objects postulated to be in the vicinity of nuclear power plants is developed. An improved tornado wind field model satisfied the no slip ground boundary condition of fluid mechanics and includes the functional dependence of eddy viscosity with altitude. Subscale wind tunnel data are obtained for all of the missiles currently specified for nuclear plant design. Confirmatory full-scale data are obtained for a 12 inch pipe and automobile. The original six degree of freedom trajectory model is modified to include the improved wind field and increased capability as to body shapes and inertial characteristics that can be handled. The improved trajectory model is used to calculate maximum credible speeds, which for all of the heavy missiles are considerably less than those currently specified for design. Equivalent coefficients for use in three degree of freedom models are developed and the sensitivity of range and speed to various trajectory parameters for the 12 inch diameter pipe are examined.

Redmann, G. H.↗

Accounting for erroneous model structures in biokinetic process models

In engineering practice, model-based design requires not only a good process-based model, but also a good description of stochastic disturbances and measurement errors to learn credible parameter values from observations. However, typical methods use Gaussian error models, which often cannot describe the complex temporal patterns of residuals. Consequently, this results in overconfidence in the identified parameters and, in turn, optimistic reactor designs. Here, we assess the strengths and weaknesses of a method to statistically describe these patterns with autocorrelated error models. This method produces increased widths of the credible prediction intervals following the inclusion of the bias term, in turn leading to more conservative design choices. However, we also show that the augmented error model is not a universal tool, as its application cannot guarantee the desired reliability of the resulting wastewater reactor design.

42 ENGINEERING↗

An arbitrary Lagrange-Eulerian investigation of HRAM shallow jet pre-spurt formation and time sensitivities to impact plate dynamics

With dry bay fires persisting as a significant contributor to aircraft vulnerability despite chronicled developments in survivability technologies, an accurate fire prediction capability remains paramount for credible vulnerability assessments. Physics based modeling of the hydrodynamic ram (HRAM) fluid deposition process is a key component of such capability, wherein capturing the first instance of fluid spurt, referred to herein as shallow jet spurts, is a core focus. Such pre-spurts as they have been formerly identified have only been witnessed sporadically in HRAM spurt experiments. In this work, ALE3D, a first-principles multi-physics code was employed to model the shallow jet spurt phenomenon with spherical projectiles impacting water-filled tanks faced with aluminum panels, such that the underlying physics and sensitivities could be explored. Development and verification of the 2D axisymmetric model is described relative to trends observed in a prior experimental campaign. Results from the verified model suggest shallow jet spurts have at least a quadratic sensitivity to the fundamental vibrational mode of the impact plate across impact velocities 610–1829 m/s (2000–6000 ft/s). It is further explained how shallow jet spurts are arrested for impacts at the two extremes of plate rigidity. This research constitutes the first fluid-structure modeling of shallow jet spurts which future three-dimensional analyses will expound upon.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Probing the Extragalactic Mid-infrared Background with HAWC

The extragalactic background light (EBL) contains all the radiation emitted by nuclear and accretion processes in stars and compact objects since the epoch of recombination. Measuring the EBL density directly is challenging, especially in the near-to-far-infrared wave band, mainly due to the zodiacal light foreground. Instead, gamma-ray astronomy offers the possibility to indirectly set limits on the EBL by studying the effects of gamma-ray absorption in the very high energy (VHE: >100 GeV) spectra of distant blazars. The High Altitude Water Cherenkov Gamma Ray Observatory (HAWC) is one of the few instruments sensitive to gamma rays with energies above 10 TeV. This offers the opportunity to probe the EBL in the near/mid-IR region: λ = 1–100 μm. In this study, we fit physically motivated emission models to Fermi-LAT gigaelectronvolt data to extrapolate the intrinsic teraelectronvolt spectra of blazars. We then simulate a large number of absorbed spectra for different randomly generated EBL model shapes and calculate Bayesian credible bands in the EBL intensity space by comparing and testing the agreement between the absorbed spectra and HAWC extragalactic observations of two blazars. The resulting bands are in agreement with current EBL lower and upper limits, showing a downward trend toward higher wavelength values λ > 10 μm also observed in previous measurements.

79 ASTRONOMY AND ASTROPHYSICS↗

JPL Thermal Design Modeling Philosophy and NASA-STD-7009 Standard for Models and Simulations - A Case Study

The Standard JPL thermal engineering practice prescribes worst-case methodologies for design. In this process, environmental and key uncertain thermal parameters (e.g., thermal blanket performance, interface conductance, optical properties) are stacked in a worst case fashion to yield the most hot- or cold-biased temperature. Thus, these simulations would represent the upper and lower bounds. This, effectively, represents JPL thermal design margin philosophy. Uncertainty in the margins and the absolute temperatures is usually estimated by sensitivity analyses and/or by comparing the worst-case results with "expected" results. Applicability of the analytical model for specific design purposes along with any temperature requirement violations are documented in peer and project design review material. In 2008, NASA released NASA-STD-7009, Standard for Models and Simulations. The scope of this standard covers the development and maintenance of models, the operation of simulations, the analysis of the results, training, recommended practices, the assessment of the Modeling and Simulation (M&S) credibility, and the reporting of the M&S results. The Mars Exploration Rover (MER) project thermal control system M&S activity was chosen as a case study determining whether JPL practice is in line with the standard and to identify areas of non-compliance. This paper summarizes the results and makes recommendations regarding the application of this standard to JPL thermal M&S practices.

thermal blanket performance↗

CAMFeND: Credibility-Aware Multimodal Fake News Detection with Rotational Attention

In the evolving digital landscape, fake news is a significant challenge, influencing public perception and decision-making. Traditional detection approaches focus on single-modal data or simple multimodal fusion, often overlooking deeper interactions and news credibility. We propose a novel model addressing these limitations by introducing rotational attention and news domain information as a feature. Unlike static attention mechanisms, our rotational attention dynamically shifts query, key, and value roles across text and image inputs, enabling richer cross-modal interaction. Incorporating news domain information further enhances the model’s reliability by associating news posts with top domains extracted from Google search results, reducing false detections. This approach assesses both the content and the broader web context in which the news is discussed. Our model outperforms existing state-of-the-art methods by providing deeper, layered multimodal integration and domain information analysis, resulting in a more robust and adaptive fake news detection system.

Gupta, Nidhi↗

A non-cooperative meta-modeling game for automated third-party calibrating, validating and falsifying constitutive laws with parallelized adversarial attacks

The evaluation of constitutive models, especially for high-risk and high-regret engineering applications, requires efficient and rigorous third-party calibration, validation and falsification. While there are numerous efforts to develop paradigms and standard procedures to validate models, difficulties may arise due to the sequential, manual, and often biased nature of the commonly adopted calibration and validation processes, thus slowing down data collections, hampering the progress towards discovering new physics, increasing expenses and possibly leading to misinterpretations of the credibility and application ranges of proposed models. This work attempts to introduce concepts from game theory and machine learning techniques to overcome many of these existing difficulties. Here, we introduce an automated meta-modeling game where two competing AI agents systematically generate experimental data to calibrate a given constitutive model and to explore its weakness such that the experiment design and model robustness can be improved through competitions. The two agents automatically search for the Nash equilibrium of the meta-modeling game in an adversarial reinforcement learning framework without human intervention. In particular, a protagonist agent seeks to find the more effective ways to generate data for model calibrations, while an adversary agent tries to find the most devastating test scenarios that expose the weaknesses of the constitutive model calibrated by the protagonist. By capturing all possible design options of the laboratory experiments into a single decision tree, we recast the design of experiments as a game of combinatorial moves that can be resolved through deep reinforcement learning by the two competing players. Our adversarial framework emulates idealized scientific collaborations and competitions among researchers to achieve a better understanding of the application range of the learned material laws and prevent misinterpretations caused by conventional AI-based third-party validation. Numerical examples are given to demonstrate the wide applicability of the proposed meta-modeling game with adversarial attacks on both human-crafted constitutive models and machine learning models.

97 MATHEMATICS AND COMPUTING↗

Refined Mass and Geometric Measurements of the High-mass PSR J0740+6620

We report results from continued timing observations of PSR J0740+6620, a high-mass, 2.8 ms radio pulsar in orbit with a likely ultracool white dwarf companion. Our data set consists of combined pulse arrival-time measurements made with the 100 m Green Bank Telescope and the Canadian Hydrogen Intensity Mapping Experiment telescope. We explore the significance of timing-based phenomena arising from general relativistic dynamics and variations in pulse dispersion. When using various statistical methods, we find that combining∼1.5 yr of additional, high-cadence timing data with previous measurements confirms and improves on previous estimates of relativistic effects within the PSR J0740+6620 system, with the pulsar mass=-+mM2.08p0.070.07 M (68.3% credibility) determined by the relativistic Shapiro time delay. For the first time, we measure secular variation in the orbital period and argue that this effect arises from apparent acceleration due to significant transverse motion. After incorporating contributions from Galactic differential rotation and off-plane acceleration in the Galactic potential, we obtain a model-dependent distance of=-+d1.140.150.17kpc (68.3% credibility). This improved distance confirms the ultracool nature of the white dwarf companion determined from recent optical observations. We discuss the prospects for future observations with next-generation facilities, which will likely improve the precision on mp for J0740+6620 by an order of magnitude within the next few years

Neutron stars↗

Comments on "The Sensitivity Study of Radiative-Convective Equilibrium in the Tropics with a Convective Resolving Model"

In general, there are two broad scientific objectives when using cloud resolving models (CRMs or cloud ensemble models-CEMs) to study tropical convection. The first one is to use them as a physics resolving models to understand the dynamic and microphysical processes associated with the tropical water and energy cycles and their role in the climate system. The second approach is to use the CRMs to improve the representation of moist processes and their interaction with radiation in large-scale models. In order to improve the credibility of the CRMs and achieve the above goals, CRMs using identical initial conditions and large-scale influences need to produce very similar results. Two CRMs produced different statistical equilibrium (SE) states even though both used the same initial thermodynamic and wind conditions. Sensitivity tests to identify the major physical processes that determine the SE states for the different CRM simulations were performed. Their results indicated that atmospheric horizontal wind is treated quite differently in these two CRMs. The model that had stronger surface winds and consequently larger latent and sensible heat fluxes from the ocean produced a warmer and more humid modeled thermodynamic SE state. In addition, the domain mean thermodynamic state is more unstable for those experiments that produced a warmer and more humid SE state. Their simulated wet (warm and humid) SE states are thermally more stable in the lower troposphere (from the surface to 4-5 km in altitude). The large-scale horizontal advective effects on temperature and water vapor mixing ratio are needed when using CRMs to perform long-term integrations to study convective feedback under specified large-scale environments. In addition, it is suggested that the dry and cold SE state simulated was caused by enhanced precipitation but not enough surface evaporation. We find some problems with the interpretation of these three phenomena.

Tao, W.-K.↗

Amundsen Sea Embayment ice-sheet mass-loss predictions to 2050 calibrated using observations of velocity and elevation change

Mass loss from the Amundsen Sea Embayment of the West Antarctic Ice Sheet is a major contributor to global sea-level rise (SLR) and has been increasing over recent decades. Predictions of future SLR are increasingly modelled using ensembles of simulations within which model parameters and external forcings are varied within credible ranges. Accurately reporting the uncertainty associated with these predictions is crucial in enabling effective planning for, and construction of defences against, rising sea levels. Calibrating model simulations against current observations of ice-sheet behaviour enables the uncertainty to be reduced. Here we calibrate an ensemble of BISICLES ice-sheet model simulations of ice loss from the Amundsen Sea Embayment using remotely sensed observations of surface elevation and ice speed. Each calibration type is shown to be capable of reducing the 90% credibility bounds of predicted contributions to SLR by 34 and 43% respectively.

54 ENVIRONMENTAL SCIENCES↗

Verification and Validation of Open-Source Computational Fluid Dynamics Capabilities in MOOSE

The Multiphysics Object Oriented Simulation Environment (MOOSE) advances predictive modeling in nuclear research by simplifying the application design process and making modeling more efficient and accessible to researchers and the broader community. Because of MOOSE’s critical role in the scientific computation field, verification and validation are important to evaluate the reliability and credibility of MOOSE’s code, simulations, and models. To assess MOOSE’s Navier Stokes module and turbulence models, the following verification and validation University of Manchester ERCOFTAC cases were simulated in MOOSE, and the results were compared: Case 032 Turbulent Flow in a 2D Channel Case 079 Natural Convection in an Enclosed Cavity

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗

Improved Compaction Experiments and Modeling of Waste Isolation Pilot Plant Standard, Non-degraded, Waste Containers

A credible simulation of disposal room porosity at the Waste Isolation Pilot Plant (WIPP) requires a tenable compaction model for the 55-gallon waste containers within the room. A review of the legacy waste material model, however, revealed several out-of-date and untested assumptions that could affect the model’s compaction behavior. For example, the legacy model predicted non-physical tensile out-of-plane stresses under plane strain compression. (Plane strain compression is similar to waste compaction in the middle of a long drift.) Consequently, a suite of new compaction experiments were performed on containers filled with surrogate, non-degraded, waste. The new experiments involved uniaxial, triaxial, and hydrostatic compaction tests on quarter-scale and full-scale containers. Special effort was made to measure the volume strain during uniaxial and triaxial tests, so that the lateral strain could be inferred from the axial and volume strain. These experimental measurements were then used to calibrate a pressure dependent, viscoplastic, constitutive model for the homogenized compaction behavior of the waste containers. This new waste material model’s predictions agreed far better with the experimental measurements than the legacy model’s predictions, especially under triaxial and hydrostatic conditions. Under plane strain compression, the new model predicted reasonable compressive out-of-plane stresses, instead of tensile stresses. Moreover, the new model’s plane strain behavior was substantially weaker for the same strain, yet substantially stronger for the same porosity, than the legacy model’s behavior. Although room for improvement exists, the new model appears ready for prudent engineering use.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗