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Contents include the following: Computing Information and Communications Technology (CICT) Systems Analysis. Our modeling approach: a 3-part schematic investment model of technology change, impact assessment and prioritization. A whirlwind tour of our model. Lessons learned.
The project goal includes developing model pathways to improve sustainability of feedstock supply chains to reduce access costs and the environmental footprint. The project aims to harness synergies of production and collection practices and current systems to improve economic and environmental outcomes.
We present a novel analysis for cluster cosmology that fully forward models the abundances, weak lensing, and the clustering of galaxy clusters. Our analysis notably includes an empirical model for the anisotropic boosts impacting the lensing and clustering signals of optical clusters. These boosts arise from a preferential selection of clusters surrounded by anisotropic large-scale structure, a consequence of the limited discrimination between line-of-sight interlopers and true cluster members offered by photometric surveys. We validate our analysis via a blind cosmology challenge on mocks, and find that we can obtain tight and unbiased cosmological constraints without informative priors or external calibrations on any of our model parameters. We then apply our analysis on the SDSS redMaPPer clusters, and find results favoring low Ωm and high σ8, combining to yield the lensing strength constraint $S_8 = 0.715_{-0.021}^{+0.024}$. We investigate potential drivers behind these results through a series of post-unblinding tests, noting that our results are consistent with existing cluster cosmology constraints but clearly inconsistent with other CMB/LSS based cosmology results. From these tests, we find hints that a suppression in the cluster lensing signal may be driving our results.
The optimal control model for pilot/vehicle analysis is used to explore the effects of a CGI visual system and motion system dynamics on helicopter hover simulation fidelity. This is accomplished by expanding the perceptual aspects of the model to include motion sensing and by relating CGI parameters to information processing parameters of the model. Simulator fidelity is examined by comparing predicted performance and workload for flight with that predicted for various simulator configuration. The results of the analysis suggest that simulator deficiencies or a reasonable nature (by current standards) can result in substantial performance and/or workload infidelity. Both CGI and motion system effects are significant for this task. There is also a distinct interaction between the two sources of pilot cues. In particular, the presence of motion reduces the sensitivity to CGI limitations.
NASTRAN computer program applications in stress analysis performed on Skylab hardware
Formal verfication and simulation are powerful tools to validate requirements against complex systems. [Problem] Requirements are developed in early stages of the software lifecycle and are typically written in ambiguous natural language. There is a gap between such requirements and formal notations that can be used by verification tools, and lack of support for proper association of requirements with software artifacts for verification. [Principal idea] We propose to write requirements in an intuitive, structured natural language with formal semantics, and to support formalization and model/code verification as a smooth, well-integrated process. [Contribution] We have developed an end-to-end, open source requirements analysis framework that checks Simulink models against requirements written in structured natural language. Our framework is built in the Formal Requirements Elicitation Tool (fret); we use fret's requirements language named fretish, and formalization of fretish requirements in temporal logics. Our proposed framework contributes the following features: 1) automatic extraction of Simulink model information and association of fretish requirements with target model signals and components; 2) translation of temporal logic formulas into synchronous dataflow cocospec specifications as well as Simulink monitors, to be used by verification tools; we establish correctness of our translation through extensive automated testing; 3) interpretation of counterexamples produced by verification tools back at requirements level. These features support a tight integration and feedback loop between high level requirements and their analysis. We demonstrate our approach on a major case study: the Ten Lockheed Martin Cyber-Physical, aerospace-inspired challenge problems.
Standard discrete event simulation is commonly used to identify system bottlenecks and starving and blocking conditions in resources and services. The CONFIG hybrid discrete/continuous simulation tool can simulate such conditions in combination with inputs external to the simulation. This provides a means for evaluating the vulnerability to system accidents of a system's design, operating procedures, and control software. System accidents are brought about by complex unexpected interactions among multiple system failures , faulty or misleading sensor data, and inappropriate responses of human operators or software. The flows of resource and product materials play a central role in the hazardous situations that may arise in fluid transport and processing systems. We describe the capabilities of CONFIG for simulation-time linear circuit analysis of fluid flows in the context of model-based hazard analysis. We focus on how CONFIG simulates the static stresses in systems of flow. Unlike other flow-related properties, static stresses (or static potentials) cannot be represented by a set of state equations. The distribution of static stresses is dependent on the specific history of operations performed on a system. We discuss the use of this type of information in hazard analysis of system designs.
The U.S. Department of Energy (DOE) Office of Nuclear Energy Office of Spent Fuel and Waste Disposition's Integrated Waste Management System (IWMS) program is applying integrated waste management system architecture analysis, system engineering, and decision analysis principles to inform potential future decisions regarding potential nuclear waste management system architectures. Architecture analyses of the IWMS are being conducted to support the future deployment of a comprehensive system for managing nuclear waste that considers all major aspects of the back end of the nuclear fuel cycle (i.e., transportation, storage, and disposal). The system architecture analyses consider alternative disposition pathways for commercial spent nuclear fuel (SNF) being stored dry in at-reactor Independent Spent Fuel Storage Installations (ISFSIs) or wet in spent-fuel pools. One method for evaluating these alternatives is simulating the movement of SNF throughout the system components. Successfully simulating a system on the scale of a national waste management system requires - accurate baseline information (e.g., historic fuel discharges from reactors and dry storage loadings at reactor sites), - modeling all logistic interactions between components of the proposed system, and - tracking and reporting all relevant details regarding the simulation's execution. The Next Generation System Analysis Model (NGSAM) is an agent-based simulation software tool designed for the express purpose of modeling the IWMS. It is based on the Performance Analysis Tool, a simulation platform that has been used to model logistics for the Department of Defense and the Federal Emergency Management Agency. Using existing, government-owned software allows NGSAM developers to modify the software at the level of source code and to develop flexible usability and modeling solutions for developing and running simulations of the IWMS. NGSAM imports data from the Oak Ridge National Laboratory (ORNL) Unified Database (e.g., historic assembly information, thermal profiles for assembly heat, at-reactor dry storage loadings) to ensure that the simulation initializes with a realistic representation of the state of commercial SNF in the United States. NGSAM is designed with the flexibility to model and track the behavior of virtually any IWMS architecture assumptions or design considerations. For example, NGSAM can model multiple interim storage facilities or repositories or none at all. Similarly, all assumptions regarding shipment schedules, operating schedules, and reactor operation assumptions can be modeled and adjusted in NGSAM with relative ease. The development of NGSAM was targeted to waste management system analysts as the primary users. With that in mind, analysts from ORNL, Sandia National Laboratories (SNL), and Argonne National Laboratory (ANL) were intimately involved in the development process. That involvement extended beyond merely defining requirements. System analysts have been involved with design decisions and software benchmarking and tests, and they have provided subject-matter expertise where necessary. The result is a high degree of interaction between professional software developers and system analysts, with a multitude of benefits to both groups. This paper explores some of the underlying methodology of the agile software development process used in the creation of NGSAM. It illustrates the capabilities of NGSAM. Some example use cases are discussed as well, with relevant results providing context for how NGSAM is used by system analysts to gain a greater understanding of alternative waste management system architectures. This is a technical paper that does not take into account the contractual limitations under the Standard Contract for Disposal of Spent Nuclear Fuel and/or High-Level Radioactive Waste (Standard Contract) (10 CFR Part 961). Under the provisions of the Standard Contract, DOE does not consider spent nuclear fuel in multi-assembly canisters to be an acceptable waste form, absent a mutually agreed-to contract amendment. To the extent discussions or recommendations in this paper conflict with the provisions of the Standard Contract, the Standard Contract provisions prevail. (authors)
This presentation is to be used in Feynman Center outreach discussions. It describes public information about some Los Alamos interests and activities in modeling and analysis in energy systems including carbon capture and direct air capture. In particular this addresses the CCSI2 project’s open-source toolkit and ongoing partnerships, as well as summarizing the published Feynman Center capability snapshot on direct air capture.
Here, we have created a forward model for charge-exchange impurity density measurements that incorporates neutral beam attenuation measurements self-consistently for the purpose of determining the ion-effective charge Z eff . The model is constructed within an integrated data analysis framework to include a self-consistent calculation of neutral beam attenuation due to multiple impurity species into the measurement of a single impurity density. The model includes measurements of the beam Doppler-shift spectrum and shine-through particle flux to determine the neutral beam particle density which is attenuated by ion collisions. Synthetic data are generated from the diagnostic forward model using statistical and calibration uncertainties. These “noisy” data are used in the analysis to evaluate how accurately Z eff is determined. Methods of experimental design are employed to calculate the information gained from different diagnostic combinations. The analysis shows that while attenuation measurements alone do not provide a unique impurity density measurement in the case of a multispecies inhomogeneous plasma, they do provide an effective measurement of the Z eff profile and place constraints on the impurity density profiles.
ABSTRACT Recovering credible cosmological parameter constraints in a weak lensing shear analysis requires an accurate model that can be used to marginalize over nuisance parameters describing potential sources of systematic uncertainty, such as the uncertainties on the sample redshift distribution n(z). Due to the challenge of running Markov chain Monte Carlo (MCMC) in the high-dimensional parameter spaces in which the n(z) uncertainties may be parametrized, it is common practice to simplify the n(z) parametrization or combine MCMC chains that each have a fixed n(z) resampled from the n(z) uncertainties. In this work, we propose a statistically principled Bayesian resampling approach for marginalizing over the n(z) uncertainty using multiple MCMC chains. We self-consistently compare the new method to existing ones from the literature in the context of a forecasted cosmic shear analysis for the HSC three-year shape catalogue, and find that these methods recover statistically consistent error bars for the cosmological parameter constraints for predicted HSC three-year analysis, implying that using the most computationally efficient of the approaches is appropriate. However, we find that for data sets with the constraining power of the full HSC survey data set (and, by implication, those upcoming surveys with even tighter constraints), the choice of method for marginalizing over n(z) uncertainty among the several methods from the literature may modify the 1σ uncertainties on Ωm–S8 constraints by ∼4 per cent, and a careful model selection is needed to ensure credible parameter intervals.
Continual advances in rotorcraft performance, vibration and acoustic characteristics are being sought by rotary-wing vehicle manufacturers to improve efficiency, handling qualities and community noise acceptance of their products. The rotor system aerodynamic and dynamic behavior are among the key factors which must be addressed to meet the desired goals. Rotor aerodynamicists study how airload redistribution impacts performance and noise, and seek ways to achieve better airload distribution through changes in local aerodynamic response characteristics. One method currently receiving attention is the use of trailing-edge flaps mounted on the rotor blades to provide direct control of a portion of the spanwise lift characteristics. The following work describes the incorporation of a trailing-edge flap model in the CAMRAD.Mod1/FHUS comprehensive rotorcraft analysis code. The CAM-RAD.Mod1/HIRES analysis consists of three separate executable codes. These include the comprehensive trim analysis, CAMRAD.Mod1, the Indicial Post-Processor, IPP, for high resolution airloads, and AIRFOIL, which produces the rotor airfoil tables from input airfoil section characteristics. The modifications made to these components permitting analysis of flapped rotor configurations are documented herein along with user instructions detailing the new input variables and operational notes.
Methane (CH4) is the second most important anthropogenic greenhouse gas (GHG). Its 100-year global warming potential (GWP) is 25 times larger than that for carbon dioxide. The 100-yr integrated GWP of CH4 is sensitive to changes in OH levels. Methane's atmospheric growth rate was estimated to be more than 10 ppb yr(exp -1) in 1998 but less than zero in 2001, 2004 and 2005 (Kirschke et al., 2013). Since 2006, the CH4 is increasing again. This phenomena is yet not well understood. Oxidation of CH4 by OH is the main loss process, thus affecting the oxidizing capacity of the atmosphere and contributing to the global ozone background. Current models typically use an annual cycle of offline OH fields to simulate CH4. The implemented OH fields in these models are typically tuned so that simulated CH4 growth rates match that measured. For future and climate simulations, the OH tuning technique may not be suitable. In addition, running full chemistry, multi-decadal CH4 simulations is a serious challenge and currently, due to computational intensity, almost impossible.
Hydrodynamic models in coastal and estuarine systems are typically constrained by sparse bathymetry, boundary, and validation data, especially in regions where field campaigns are costly or impractical. Here we develop and test a fully satellite-driven framework for hydrodynamic modeling in South Africa’s Langebaan Lagoon without using any local in situ measurements. Bathymetry is derived by training multispectral Sentinel-2 reflectance against ICESat-2 ATL24 photon-derived depths using an XGBoost model optimized with Bayesian search. The final satellite-derived bathymetry reproduces independent ATL24 points with RMSE = 0.45 m and R 2 = 0.97. This bathymetry was used in a depth-averaged Delft3D Flexible Mesh model driven at the open boundary by TPXO tidal harmonics and by ERA5 winds. We validate modeled water surface elevation against 16 SWOT low-rate (250 m, unsmoothed) passes in 2023. SWOT–model comparisons yield an overall RMSE of 0.11 m and R 2 = 0.61, with typical point differences <0.10 m (∼7% of the 1.5 m tidal range), and showed consistent spatial gradients in water level from the offshore boundary, through Saldanha Bay, and into the lagoon. At the offshore boundary, TPXO and SWOT sea surface heights agree closely (R 2 = 0.86). A simple phase adjustment of ∼26,min between TPXO and SWOT lowers the RMSE from 0.18,m to 0.11,m, showing that phase offset accounts for some of the discrepancy, with additional errors likely linked to non-tidal signals. Our results demonstrate that combining passive optical, photon-counting LiDAR, radar interferometry, and global tidal/atmospheric models enables robust, transferrable hydrodynamic modeling in data-scarce coastal systems, offering a cost-effective pathway for monitoring.
The reliability of chemical processes can be greatly improved by implementing inline monitoring systems. Combining multivariate analysis with non-destructive sensors can enhance the process without interfering with the operation. Here, we present here hierarchical models using both principal component analysis and partial least square analysis developed for different chemical components representative of solvent extraction process streams. A training set of 380 samples and an external validation set of 95 samples were prepared and Near infrared and Raman spectral data as well as conductivity under variable temperature conditions were collected. The results from the models indicate that careful selection of the spectral range is important. By compressing the data through Principal Component Analysis (PCA), we lower the rank of the data set to its most dominant features while maintaining the key principal components to be used in the regression analysis. Within the studied data set, concentration of five chemical components were modeled; total nitrate (NO 3 - ), total acid (H + ), neodymium (Nd 3+ ), sodium (Na + ), and ionic strength (I.S.). The best overall model prediction for each of the species studied used a combined data set comprised of complementary techniques including NIR, Raman, and conductivity. Finally, our study shows that chemometric models are powerful but requires significant amount of carefully analyzed data to capture variations in the chemistry.
The Gateway Integrated ECLSS Model (GIEM) is a set of two independent models, made in Aspen Custom Modeler (ACM) and Thermal Desktop (TD), of the Gateway stack and each modules' associated environment control and life support system (ECLSS). The GIEM utilizes the 41-Node Metabolic Man (METMAN) to simulate crew inside the Gateway consuming O2 and producing CO2, H2O, and heat for the ECLSS to remove. The modules and visiting vehicles all have different levels of ECLSS capabilities and may rely on other modules and Intermodular Ventilation (IMV), which is used to exchange gas between the modules, to ensure the entire Gateway environment is controlled. If IMV were to fail or be turned off, some vehicles may have limited access to necessary ECLSS functions. This analysis focuses on evaluating O2, CO2, and H2O levels when crew are in vehicles without their own life support and IMV has failed to evaluate how long before the atmosphere is unsafe for the crew. This analysis uses the integrated nature of the GIEM to look at time to effect for O2 depletion and CO2 and H2O buildup when crew are working in vehicles that have been cut off from the ECLSS-active portion of the stack. This information is used to inform for how long crew can safely continue working in the ECLSS-inactive vehicles before experiencing a requirement violation or physical limitation and can be referenced when developing maintenance and emergency response concept of operations (ConOps).
A model of the VF5 test facility at NASA Glenn Research Center was developed using the direct simulation Monte Carlo Hypersonic Aerothermodynamics Particle (HAP) code. The model results were compared to several cold flow and thruster hot fire cases. The main uncertainty in the model is the determination of the effective sticking coefficient -- which sets the pumping effectiveness of the cryopanels and oil diffusion pumps including baffle transmission. An effective sticking coefficient of 0.25 was found to provide generally good agreement with the experimental chamber pressure data. The model, which assumes a cold diffuse inflow, also fared satisfactorily in predicting the pressure distribution during thruster operation. The model was used to assess other chamber configurations to improve the local effective pumping speed near the thruster. A new configuration of the existing cryopumps is found to show more than 2x improvement over the current baseline configuration.
Manual control of rendezvous and docking (RVD) of two spacecraft in low earth orbit by a remote human operator is discussed. Experimental evidence has shown that control performance degradation for large transmission delays (between spacecraft and operations control center) can be substantially improved by the introduction of predictor displays. An intial Optimal Control Model (OCM) analysis of RVD translational and rotational perturbation control was performed, with emphasis placed on the predictive capabilities of the combined Kalman estimator/optimal predictor with respect to control performance, for a range of time delays, motor noise levels and tracking axes. OCM predictions are then used as a reference for comparing tracking performance with a simple predictor display, as well as with no display prediction at all. Use is made here of an imperfect internal model formulation, whereby it is assumed that the human operator has no knowledge of the system transmission delay.