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DOE OSTI2019

Metalearners for estimating heterogeneous treatment effects using machine learning

There is growing interest in estimating and analyzing heterogeneous treatment effects in experimental and observational studies. We describe a number of metaalgorithms that can take advantage of any supervised learning or regression method in machine learning and statistics to estimate the conditional average treatment effect (CATE) function. Metaalgorithms build on base algorithms—such as random forests (RFs), Bayesian additive regression trees (BARTs), or neural networks—to estimate the CATE, a function that the base algorithms are not designed to estimate directly. We introduce a metaalgorithm, the X-learner, that is provably efficient when the number of units in one treatment group is much larger than in the other and can exploit structural properties of the CATE function. For example, if the CATE function is linear and the response functions in treatment and control are Lipschitz-continuous, the X-learner can still achieve the parametric rate under regularity conditions. We then introduce versions of the X-learner that use RF and BART as base learners. In extensive simulation studies, the X-learner performs favorably, although none of the metalearners is uniformly the best. In two persuasion field experiments from political science, we demonstrate how our X-learner can be used to target treatment regimes and to shed light on underlying mechanisms. A software package is provided that implements our methods.

42 ENGINEERING↗

NASA NTRS2005

Minimizing Uncertainty in Cryogenic Surface Figure Measurement

A new facility at the Goddard Space Flight Center is designed to measure with unusual accuracy the surface figure of mirrors at cryogenic temperatures down to 12 K. The facility is currently configured for spherical mirrors with a radius of curvature (ROC) of 600 mm, and apertures of about 150 mm or less. The goals of the current experiment were to 1) Obtain the best possible estimate of test mirror surface figure, S(x,y) at 87 K and 20 K; 2) Obtain the best estimate of the cryo-change, Delta (x,y): the change in surface figure between room temperature and the two cryo-temperatures; and 3) Determine the uncertainty of these measurements, using the definitions and guidelines of the ISO Guide to the Expression of Uncertainty in Measurement. A silicon mirror was tested, and the cry-change from room temperature to 20K was found to be 3.7 nm rms, with a standard uncertainty of 0.23 nm in the rms statistic. Both the cryo-change figure and the uncertainty are among the lowest such figures yet published. This report describes the facilities, experimental methods, and uncertainty analysis of the measurements.

Blake, Peter↗

DOE OSTI2024

Timelike Compton Scattering from a longitudinally polarised target with CLAS12 at Jefferson Lab

Explorations into the internal dynamics of hadrons are constantly evolving, and the requirement for experimental results to verify theoretical models of hadron structure is paramount. A key area in this field is the study of Generalised Parton Distributions (GPDs), which are functions used to model the momenta of quarks and gluons within hadrons, and the methods to access GPDs experimentally. One such scattering process that allows access to these is Timelike Compton Scattering. TCS complements existing Deeply Virtual Compton Scattering experiments and allows investigation into the universality of GPDs through access to the real and imaginary parts of the parton helicity independent GPD Hq via beam spin asymmetries (BSA), and it provides novel access to the real and imaginary parts of the parton helicity dependent GPD ˜Hq through target polarisation asymmetries (TSA). This thesis work presents a comparative study with the first published BSA for TCS at the Thomas Jefferson National Accelerator Facility (JLab), alongside a first time extraction of a Target Spin Asymmetry with the Summer 2022 data taking run. JLab hosts the Continuous Electron Beam Accelerator Facility (CEBAF) which provides a 12 GeV electron beam to four experimental halls. Hall-B contains the CEBAF Large Acceptance Spectrometer, which took data across three run periods on a longitudinally polarised NH3 and ND3 fixed target from 2022-2023, to extract measurements of electron-proton scattering, from which a TCS signal could be extracted. The thesis discusses work done to understand and eliminate contributions from the non-/low-polarised nuclear background, testing pre-established cuts to eliminate pion background from a dilepton (e+e-) final state and modifying them as needed for the new experimental run, and attempts to hone in on a clean TCS signal from which to extract the two asymmetry observables. A comparison with existing BSA results was performed; however, the statistical errors are too large to draw a significant conclusion as to whether there is agreement across each bin. More data is needed for a multidimensionally binned extraction. A proof of principle was achieved in the TSA measurements, with two out of four kinematic bins showing preliminary agreement in shape with theoretical values. Again, the errors are significant due to the contributions from the nuclear background. To support these conclusions, a further study was done, which takes into account an estimate of the asymmetries with the full available dataset (this thesis is based only on data taken in the summer set; at the time of writing processing was still being conducted for the final two datasets), as well as an estimate including additional future experiment days that were awarded in July 2024. Additional work was done on a secondary project exploring the feasibility of measuring TCS at the upcoming Electron Ion Collider, supporting the design proposal for the detector for the first interaction region and giving a positive outlook for the future of these types of measurements beyond JLab.

Gates, Kayleigh [Univ. of Glasgow, Scotland (Unite↗

DOE OSTI2022

Multi-fidelity information fusion with concatenated neural networks

Recently, computational modeling has shifted towards the use of statistical inference, deep learning, and other data-driven modeling frameworks. Although this shift in modeling holds promise in many applications like design optimization and real-time control by lowering the computational burden, training deep learning models needs a huge amount of data. This big data is not always available for scientific problems and leads to poorly generalizable data-driven models. This gap can be furnished by leveraging information from physics-based models. Exploiting prior knowledge about the problem at hand, this study puts forth a physics-guided machine learning (PGML) approach to build more tailored, effective, and efficient surrogate models. For our analysis, without losing its generalizability and modularity, we focus on the development of predictive models for laminar and turbulent boundary layer flows. In particular, we combine the self-similarity solution and power-law velocity profile (low-fidelity models) with the noisy data obtained either from experiments or computational fluid dynamics simulations (high-fidelity models) through a concatenated neural network. We illustrate how the knowledge from these simplified models results in reducing uncertainties associated with deep learning models applied to boundary layer flow prediction problems. The proposed multi-fidelity information fusion framework produces physically consistent models that attempt to achieve better generalization than data-driven models obtained purely based on data. While we demonstrate our framework for a problem relevant to fluid mechanics, its workflow and principles can be adopted for many scientific problems where empirical, analytical, or simplified models are prevalent. In line with grand demands in novel PGML principles, this work builds a bridge between extensive physics-based theories and data-driven modeling paradigms and paves the way for using hybrid physics and machine learning modeling approaches for next-generation digital twin technologies.

42 ENGINEERING↗

DOE OSTI2026

Studying MeV Scale Neutron Interactions in DUNE ND-LAr 2x2 Demonstrator

The Deep Underground Neutrino Experiment (DUNE) is a long-baseline neutrino oscillation experiment designed to make high-precision measurements of neutrino oscillation parameters and probe for new physics using a neutrino beam produced at Fermilab and measured at a near detector complex and a far detector located 1,300 km away at the Sanford Underground Research Facility. Precise neutrino energy reconstruction is essential for these measurements, with neutron production in neutrino–argon interactions representing a significant source of systematic uncertainty, as neutrons can carry away significant energy, making their detection and characterization crucial. DUNE’s near detector complex includes ND-LAr, a Liquid Argon Time Projection Chamber (LArTPC) detector designed to mirror the far detector technology and constrain neutrino–argon interaction systematics. The DUNE 2x2 Demonstrator, a pixelated LArTPC based on the ArgonCube design, serves as a prototype for ND-LAr. During 2x2 operations from October to November 2026, an Americium–Beryllium (AmBe) neutron source was deployed near the detector cryostat to obtain a high-statistics sample of neutron interactions. This poster presents progress in studying MeV-scale neutron interactions in this dataset by identifying de-excitation gammas from neutron capture on argon, providing a method for neutron identification and charge readout system calibration in future DUNE detectors.

Mao, Edgar [Syracuse U.] (ORCID:0009000600893306)↗

NASA NTRS1998

Performance of an Axisymmetric Rocket Based Combined Cycle Engine During Rocket Only Operation Using Linear Regression Analysis

The all rocket mode of operation is shown to be a critical factor in the overall performance of a rocket based combined cycle (RBCC) vehicle. An axisymmetric RBCC engine was used to determine specific impulse efficiency values based upon both full flow and gas generator configurations. Design of experiments methodology was used to construct a test matrix and multiple linear regression analysis was used to build parametric models. The main parameters investigated in this study were: rocket chamber pressure, rocket exit area ratio, injected secondary flow, mixer-ejector inlet area, mixer-ejector area ratio, and mixer-ejector length-to-inlet diameter ratio. A perfect gas computational fluid dynamics analysis, using both the Spalart-Allmaras and k-omega turbulence models, was performed with the NPARC code to obtain values of vacuum specific impulse. Results from the multiple linear regression analysis showed that for both the full flow and gas generator configurations increasing mixer-ejector area ratio and rocket area ratio increase performance, while increasing mixer-ejector inlet area ratio and mixer-ejector length-to-diameter ratio decrease performance. Increasing injected secondary flow increased performance for the gas generator analysis, but was not statistically significant for the full flow analysis. Chamber pressure was found to be not statistically significant.

Smith, Timothy D.↗

DOE OSTI2014

Storage of Ultracold Neutrons in the Magneto-Gravitational Trap of the UCN Experiment

The UCN experiment is designed to measure the lifetime n of the free neutron by trapping ultracold neutrons (UCN) in a magneto-gravitational trap. An asymmetric bowl-shaped NdFeB magnet Halbach array confines low-field-seeking UCN within the apparatus, and a set of electromagnetic coils in a toroidal geometry provides a background holding field to eliminate depolarization-induced UCN loss caused by magnetic field nodes. We present a measurement of the storage time store of the trap by storing UCN for various times and counting the survivors. The data are consistent with a single exponential decay, and we find store = 860 19 s, within 1 of current global averages for n. The storage time with the holding field deactivated is found to be store = 470 160 s; this decreased storage time is due to the loss of UCN, which undergo Majorana spin flips while being stored. We discuss plans to increase the statistical sensitivity of the measurement and investigate potential systematic effects.

Salvat, D. J.↗

DOE OSTI2017

Statistical analysis of the Nb 3 Sn strand production for the ITER toroidal field coils

The ITER toroidal field (TF) strand procurement initiated the largest Nb 3 Sn superconducting strand production hitherto. The industrial-scale production started in Japan in 2008 and finished in summer 2015. Six ITER partners (so-called Domestic Agencies, or DAs) are in charge of the procurement and involved eight different strand suppliers all over the world, of which four are using the bronze route (BR) process and four the internal-tin (IT) process. In total more than 500 tons have been produced including excess material covering losses during the conductor manufacturing process, in particular the cabling. The procurement is based on a functional specification where the main strand requirements like critical current, hysteresis losses, Cu ratio and residual resistance ratio are specified but not the strand production process or layout. We introduce the analysis on the data acquired during the quality control (QC) process that was carried out to ensure the same conductor performance requirements are met by the different strand suppliers regardless of strand design. The strand QC is based on 100% billet testing and on applying statistical process control (SPC) limits. Throughout the production, samples adjacent to the strand pieces tested by the suppliers are cross-checked ('verified') by their respective DAs reference labs. The level of verification was lowered from 100% at the beginning of the procurement progressively to approximately 25% during the final phase of production. Based on the complete dataset of the TF strand production, an analysis of the SPC limits of the critical strand parameters is made and the related process capability indices are calculated. In view of the large-scale production and costs, key manufacturing parameters such as billet yield, number of breakages and piece-length distribution are also discussed. Furthermore, the results are compared among all the strand suppliers, focusing on the difference between BR and IT processes. Following the completion of the largest Nb 3 Sn strand production, our experience gained from monitoring the execution of the QC activities and from auditing the results from the measurements is summarised for future superconducting strand material procurement activities.

Vostner, A.↗

DOE OSTI2019

Waste Chemistry Envelope for the Determination of Pitting Corrosion Susceptibility - 19554

Liquid radioactive wastes at the Hanford and Savannah River sites are stored in large underground carbon steel tanks. The high-level wastes are processed in several of the tanks and then transferred by piping to other site facilities for further processing before they are stabilized in a vitrified or grout waste form. Based on waste removal and processing schedules, many of the tanks, will be required to be in service for times exceeding the initial intended life (i.e., greater than 60 years). Until the waste is removed from storage, transferred, and processed, the materials and structures of the tanks must maintain a confinement function by providing a barrier to the environment and by maintaining acceptable structural stability during design basis events, which include loadings from both normal service and abnormal (e.g., earthquake) conditions. Administrative programs are in place to mitigate potential corrosion mechanisms and thereby maintain the structural and leak integrity functions of these waste tanks throughout their intended service life. Waste chemistry and temperature control are the means by which corrosion degradation of the waste tanks is minimized. Chemistry controls are based on in-situ coupon tests, waste tank experience, and laboratory testing. These requirements comprise the technical standards for corrosion control. The standards are utilized then as guidelines for operational procedures. The present waste chemistry controls for the Hanford DSTs were established in the 1980's in response to tank failures caused by stress corrosion cracking (SCC) at the DOE Savannah River Site (SRS). Portions of the SRS chemistry limits, which were developed at the Savannah River National Laboratory (SRNL) were coupled with corrosion testing results from Pacific Northwest National Laboratories (PNNL) and adopted for corrosion control of the double-shell tank (DST) waste at the Hanford Site. Since that time, the temperatures of the waste in the DSTs have decreased to less than 50 deg. C in most cases as the radioactive material has decayed. As a consequence, new chemistry controls were formulated for SCC in 2010. This testing however, did not address that potential for pitting in the supernatant and at the liquid-air interface. Indeed, initial tests indicated that the inhibitor requirements for SCC would be insufficient for the prevention of pitting. In addition to lower waste temperatures, future retrieval and process changes may impact the DST waste chemistry. Initial projections suggest that the waste chemistry of the DSTs may shift to a broader range of pH and higher aggressive anion concentrations (e.g., chloride, sulfate, etc.) than the wastes that are presently stored. Additionally, processes within the vitrification facility may result in streams that are returned to the tank farm for evaporation. These streams may also contain high concentrations of aggressive species. SRNL investigated the propensity for pitting of the carbon steel waste tanks at current and projected DST waste chemistries. A statistically designed series of tests provided a pitting factor that relates the ratio of the inhibitor species to the aggressive species and the probability of observing pitting. An acceptable pitting factor was determined and was utilized for the development of a new chemistry envelope. The new chemistry envelope was compared to the envelope that was established for SCC and was determined to be bounding. Validation of the new chemistry envelope was performed via model simulations and comparison with historical experimental results and approaches to establishing chemistry envelopes. The new chemistry envelope will eventually be part of an overall assessment of the condition of the tanks and any changes made to the overall structural integrity program for the Hanford DSTs. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2018

Photochemical Kinetic Modeling of Degradation of Aqueous Polyvinyl Alcohol in a UV/H{sub 2}O{sub 2} Photoreactor

This study presents a photochemical kinetics model to describe the degradation of water-soluble PVA (Polyvinyl Alcohol) polymer in a UV/H{sub 2}O{sub 2} batch reactor. Under the effect of UV light, the photolysis of hydrogen peroxide into hydroxyl radicals can generate a series of polymer scission reactions. For a better understanding and analysis of the UV/H{sub 2}O{sub 2} process in the cracking of the PVA macromolecules, a chemical reaction mechanism of the degradation process and a relevant photochemical kinetics model are developed to describe the disintegration of the polymer chains. Taking into account the probabilistic fragmentation of the polymer, the statistical moment approach is used to model the molar population balance of live and dead polymer chains. The model predicts the PVA molecular weight reduction, the acidity of the solution, and hydrogen peroxide residual. In addition to previously published data collected in this laboratory, a new set of experiments were conducted using a 500 mg/L PVA aqueous for different hydrogen peroxide/PVA ratios for model validation. Measurements of average molecular weights of the polymer, hydrogen peroxide concentrations and pH of the PVA solution were determinant factors in constructing a reliable photochemical model of the UV/H{sub 2}O{sub 2} process. Experimental data showed a decrease in the PVA molecular weight and a buildup of the solution acidity. The experimental data also served to determine the kinetics rate constants of the PVA photochemical degradation and validate the model whose predictions are in good agreement with data. The model can provide a comprehensive understanding of the impact of the design and operational variables.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Simulations of muon imaging with the LANL GMT detector for spent nuclear fuel cask content verification

Atmospheric muons are typically high energy, highly penetrating charged particles. They interact with matter primarily through multiple Coulomb scatterings. Muon scattering intensities can be used to characterize the density and atomic number of the matter that they pass through. Previously, the Los Alamos National Laboratory (LANL) muon tomography team performed muon imaging of the partially filled MC-10 spent nuclear fuel (SNF) cask at Idaho National Laboratory (INL). This experiment demonstrated the feasibility of muon imaging for the verification of spent fuel container contents. That original effort used the mini muon tracker array, consisting of two arrays of drift tubes on either side of the SNF cask. The reconstructed image quality was limited by statistics, largely due to low muon flux at high zenith angles. A LANL led team will perform new measurements with a larger array, the Giant Muon Tracker (GMT), to improve data collection rates and statistics. In this work, simulations were performed with the GMT near the partially filled INL MC-10 cask. For more general fuel diversion detection, a full MC-10 cask and casks with a singular missing fuel bundle were also simulated. To understand minimum measurement times needed for missing bundle identification, 100 000 to millions of tracked muons (corresponding to 1.4 days to several weeks measurement time) were analyzed. Simulated images were then analyzed visually and numerically to explore techniques designed to minimize the collection time needed to identify the diversion of fuel in each scenario.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2017

Deformed Materials: Towards a Theory of Materials Morphology Dynamics

This grant supported work on the response of crystals to external stress. Our primary work described how disordered structural materials break in two (statistical models of fracture in disordered materials), studied models of deformation bursts (avalanches) that mediate deformation on the microscale, and developed continuum dislocation dynamics models for plastic deformation (as when scooping ice cream bends a spoon, Fig. 9). Glass is brittle -- it breaks with almost atomically smooth fracture surfaces. Many metals are ductile -- when they break, the fracture surface is locally sheared and stretched, and it is this damage that makes them hard to break. Bone and seashells are made of brittle material, but they are strong because they are disordered -- lots of little cracks form as they are sheared and near the fracture surface, diluting the external force. We have studied materials like bone and seashells using simulations, mathematical tools, and statistical mechanics models from physics. In particular, we studied the extreme values of fracture strengths (how likely will a beam in a bridge break far below its design strength), and found that the traditional engineering tools could be improved greatly. We also studied fascinating crackling-noise precursors -- systems which formed microcracks of a broad range of sizes before they broke. Ductile metals under stress undergo irreversible plastic deformation -- the planes of atoms must slide across one another (through the motion of dislocations) to change the overall shape in response to the external force. Microscopically, the dislocations in crystals move in bursts of a broad range of sizes (termed 'avalanches' in the statistical mechanics community, whose motion is deemed 'crackling noise'). In this grant period, we resolved a longstanding mystery about the average shape of avalanches of fixed duration (using tools related to an emergent scale invariance), we developed the fundamental theory describing the shapes of avalanches and how they are affected by the edges of the microscope viewing window, we found that slow creep of dislocations can trigger an oscillating response explaining recent experiments, we explained avalanches under external voltage, and we have studied how avalanches in experiments on the microscale relate to deformation of large samples. Inside the crystals forming the metal, the dislocations arrange into mysterious cellular structures, usually ignored in theories of plasticity. Writing a natural continuum theory for dislocation dynamics, we found that it spontaneously formed walls -- much like models of traffic jams and sonic booms. These walls formed rather realistic cellular structures, which we examined in great detail -- our walls formed fractal structures with fascinating scaling properties, related to those found in turbulent fluids. We found, however, that the numerical and mathematical tools available to solve our equations were not flexible enough to incorporate materials-specific information, and our models did not show the dislocation avalanches seen experimentally. In the last year of this grant, we wrote an invited review article, explaining how plastic flow in metals shares features with other stressed materials, and how tools of statistical physics used in these other systems might be crucial for understanding plasticity.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Simple Statistical Models for Predicting Overpressure Due to CO2 and Low-Salinity Waste-Fluid Injection into Deep Saline Formations

Deep saline aquifers have been used for waste-fluid disposal for decades and are the proposed targets for large-scale CO2 storage to mitigate CO2 concentration in the atmosphere. Due to relatively limited experience with CO2 injection in deep saline formations and given that the injection targets for CO2 sometimes are the same as waste-fluid disposal formations, it could be beneficial to model and compare both practices and learn from the waste-fluid disposal industry. In this paper, we model CO2 injection in the Patterson Field, which has been proposed as a site for storage of 50 Mt of industrial CO2 over 25 years. We propose general models that quickly screen the reservoir properties and calculate pressure changes near and far from the injection wellbore, accounting for variable reservoir properties. The reservoir properties we investigated were rock compressibility, injection rate, vertical-to-horizontal permeability ratio, average reservoir permeability and porosity, reservoir temperature and pressure, and the injectant total dissolved solids (TDS) in cases of waste-fluid injection. We used experimental design to select and perform simulation runs, performed a sensitivity analysis to identify the important variables on pressure build-up, and then fit a regression model to the simulation runs to obtain simple proxy models for changes in average reservoir pressure and bottomhole pressure. The CO2 injection created more pressure compared to saline waste-fluids, when similar mass was injected. However, we found a more significant pressure buildup at the caprock-reservoir interface and lower pressure buildup at the bottom of the reservoir when injecting CO2 compared with waste-fluid injection.

Ansari, Esmail↗

NASA NTRS1990

Development of a scintillating optical fiber ionization calorimeter

A design study of a scintillation fiber (SF) calorimeter for a cosmic ray observation is made. An evaluation of various fibers and design configuration was made. The proposed design has a dimension of 1 m (W) x 1 m (L) x 16 cm (H) contains 1000 fibers at each of 40 x- or 40 y-layers interleaved with 1mm thick leadplates. Two or four CCD Particle Track Imaging Systems are connected to a bundle of SF edges at x- and y-ends. The overall weight of a calorimeter is 1,200 kg including read-out systems and supporting boards. The designed calorimeter can measure cosmic ray nuclei and gamma-rays with position, angles and energy information suitable for detailed spectrum analysis. The system is particularly beneficial at very high energies where the flux is extremely low and it requires a very long exposure over many years in space. Emulsion chambers have an advantage for cosmic ray measurements if the exposure is limited to several months in space. In fact, the most important energy region for the current cosmic ray studies is at around 1,000 TeV where a drastic change of elemental composition is indicated by various indirect observations. A detector whose size is in the order of 1 m(sup 2) requires several years of exposure in space accumulate sufficient statistics near 1,000 TeV. Emulsions will be strongly contaminated by background radiation for such a long duration flight, while SF calorimeter is totally immune from this concern. This is particularly important for long-duration experiments. The SF calorimeter also allows time-tagging of individual events, extending the experimental capability in various ways.

Takahashi, Y.↗

NASA NTRS1990

BATSE software for the analysis of the gamma ray burst spatial distribution

The Burst and Transient Source Experiment (BATSE) on the Gamma Ray Observatory (GRO) is designed to study astronomical gamma ray sources and to provide better positional, spectral, and time resolution about these objects than has previously been possible from one experiment. The procedure to be used in the analysis of the gamma ray burst spatial distribution is presented. Data is input from BATSE via the Gamma Ray Burst Catalog (listing individual burst positions, flux values, and associated errors) and the Sky Sensitivity Map (which summarizes observational selection effects in table format). A FORTRAN program generates Monte Carlo burst catalogs, which are models to be compared to the actual distribution. The Monte Carlo models are then filtered through the Sky Sensitivity Map so that they suffer from the same selection effects as the actual catalog data. Additionally, each burst position is converted into a probability distribution to mimic BATSE positional sensitivity. The Burst Catalog, Monte Carlo burst catalog, and Sky Sensitivity Map are then passed onto an IDL program that compares the catalogs for statistical significance. The Sky Sensitivity Map is used to estimate how often each sky area is observed above the minimum flux level in question. Each burst found in this sky area is then weighted according to the frequency with which this sky area is observed. The catalogs are then compared via tests of homogeneity (based on their radial distributions) and isotropy (based upon their angular distributions). The results of the statistical comparisons along with graphs and charts of the summaries, are output from the IDL program for study.

Hakkila, Jon↗

DOE OSTI2018

Optimization study for the experimental configuration of CMB-S4

The CMB Stage 4 (CMB-S4) experiment is a next-generation, ground-based experiment that will measure the cosmic microwave background (CMB) polarization to unprecedented accuracy, probing the signature of inflation, the nature of cosmic neutrinos, relativistic thermal relics in the early universe, and the evolution of the universe. CMB-S4 will consist of O (500,000) photon-noise-limited detectors that cover a wide range of angular scales in order to probe the cosmological signatures from both the early and late universe. It will measure a wide range of microwave frequencies to cleanly separate the CMB signals from galactic and extra-galactic foregrounds. To advance the progress towards designing the instrument for CMB-S4, we have established a framework to optimize the instrumental configuration to maximize its scientific output. The framework combines cost and instrumental models with a cosmology forecasting tool, and evaluates the scientific sensitivity as a function of various instrumental parameters. The cost model also allows us to perform the analysis under a fixed-cost constraint, optimizing for the scientific output of the experiment given finite resources. In this paper, we report our first results from this framework, using simplified instrumental and cost models. Here, we have primarily studied two classes of instrumental configurations: arrays of large-aperture telescopes with diameters ranging from 2–10 m, and hybrid arrays that combine small-aperture telescopes (0.5-m diameter) with large-aperture telescopes. We explore performance as a function of telescope aperture size, distribution of the detectors into different microwave frequencies, survey strategy and survey area, low-frequency noise performance, and balance between small and large aperture telescopes for hybrid configurations. Both types of configurations must cover both large (~ degree) and small (~ arcmin) angular scales, and the performance depends on assumptions for performance vs. angular scale. The configurations with large-aperture telescopes have a shallow optimum around 4–6 m in aperture diameter, assuming that large telescopes can achieve good performance for low-frequency noise. We explore some of the uncertainties of the instrumental model and cost parameters, and we find that the optimum has a weak dependence on these parameters. The hybrid configuration shows an even broader optimum, spanning a range of 4–10 m in aperture for the large telescopes. We also present two strawperson configurations as an outcome of this optimization study, and we discuss some ideas for improving our simple cost and instrumental models used here. There are several areas of this analysis that deserve further improvement. In our forecasting framework, we adopt a simple two-component foreground model with spatially varying power-law spectral indices. We estimate de-lensing performance statistically and ignore non-idealities such as anisotropic mode coverage, boundary effect, and possible foreground residual. Instrumental systematics, which is not accounted for in our analyses, may also influence the conceptual design. Further study of the instrumental and cost models will be one of the main areas of study by the entire CMB-S4 community. Finally, we hope that our framework will be useful for estimating the influence of these improvements in the future, and we will incorporate them in order to further improve the optimization.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2026

Mass Spectrometer Transient Analysis

This software implements a complete preprocessing pipeline for transient mass spectrometry (MS) data collected during TAP (Temporal Analysis of Products) experiments. It is designed to extract chemically meaningful fluxes from overlapping ion signals by applying a calibrated defragmentation matrix and solving the resulting linear system using non-negative least squares (NNLS) regression. The core script, preprocess_mass_spec.py, performs the following operations: Gain correction: Applies amplifier gain scalars derived from inert-packed calibration pulses to normalize signal intensities across AMUs and acquisition settings. Background subtraction: Removes experiment baselines using user-defined time windows, ensuring compatibility with slow-diffusing species and preventing negative values that would interfere with NNLS. Options to subtract before and after defragmentation. Defragmentation: Constructs a fragmentation matrix A from zeroth moments of calibration pulses (equal molar gas:inert mixtures) and solves Ax=b at each time point, where b is the raw MS signal and x is the estimated species flux. The matrix is normalized to inert signals and accounts for instrument-specific fragmentation behavior. Pulse-mode handling: Supports both averaged and individual pulse modes, enabling statistical treatment of fluxes and calculation of standard deviations. Integration and output: Computes zeroth moments (integrated fluxes) and exports time-resolved and integrated data in CSV format, suitable for downstream kinetic modeling. The software is validated using both virtual TAP simulations (VTAP) and experimental data from propane dehydrogenation (PDH) on CrOx/Al2O3 catalysts. It preserves temporal resolution by applying NNLS point-by-point across the pulse duration (typically 6,000+ time slices per pulse), leveraging the linear superposition principle to reconstruct full flux profiles. The defragmented outputs are compatible with kinetic extraction methods such as the G and Y procedures, which are used to derive rate–concentration relationships from TAP data. The details of these validations are discussed in detail in the supporting manuscript and supporting information. Example data and output files are also included. The methodology is robust to experimental noise and drift, with calibration protocols that account for pulse size effects, MS aging, and inert gas normalization. The software is modular, reproducible, and tailored for high-throughput TAP-MS workflows in catalysis research.

Kristy, Stephen [Idaho National Laboratory (INL), ↗

NASA NTRSDate not supplied

Impacts from Assimilating Large Volumes of GNSS Radio Occultation (RO) Observations during ROMEX in NASA’s Global Earth Observing System

The GNSS Radio Occultation (RO) Modeling Experiment (ROMEX) seeks to quantify the benefit of the increasing quantity of RO observations available for use in operational numerical weather prediction (NWP) systems and products. ROMEX includes participation from multiple operational NWP centers and NWP models, among them are NASA’s Global Earth Observing System (GEOS) model produced and run at the Global Modeling and Assimilation Office (GMAO). The design of the numerical experiments core to ROMEX include: 1) a control model run that includes all the RO observations currently used operationally with the sole exception of those from commercial sources and 2) a ROMEX model run that adds to the control over 25 thousand additional RO profiles per day from commercial RO providers, with both experiments run over the three-month period of September through November 2022. The ROMEX model run greatly augments the relatively small subset of the currently available commercial RO profiles which have been purchased for routine use in operational NWP by the various NWP centers. While this smaller subset of commercial RO profiles currently used in operations has been shown to have a positive impact on NWP forecasts, the additional impact from the ROMEX RO dataset has yet to be determined and is the focus of ROMEX. Results from GEOS are presented, including the impact on both analyses and forecasts over the study period and statistics using the forecast sensitivity-based observation impact (FSOI) method. The impact from varying the method of quality control and specifying the observation uncertainty for RO observations within the GEOS data assimilation system is also examined.

Michael J Murphy↗