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LLNL implemented infrastructure to include treatment of URR in GNDS. There are two options to store URR probabilities: cross-sections pdf and ACE-like probability tables. Issues were found with both options during verification with criticality benchmarks. Projected future steps include resolving issues in the next year and adding criticality benchmarks sensitive to URR.
The design and development of fully functional Molten-Salt Reactors (MSR) require detailed knowledge of the molten salt properties in order to understand and predict the salt’s behavior. Fundamental properties of interest include molecular structure, speciation, and dynamics (such as diffusion coefficients) of salt components and dissolved corrosion and fission products. Computer modeling is necessary to predict changes in physical and chemical properties due to irradiation, burning of dissolved fuel, and corrosion. The modeling requires experimental data, and advanced neutron and x-ray scattering and spectroscopy provide the most reliable and direct determination of the structure (Pair-Distribution Functions, PDF), and dynamics of ions in the melt. This project dealt with both fluoride and chloride salts. The PDFs have been measured by a combination of neutron and x-ray diffraction. We utilized the techniques of isotope substitutions, a very powerful tool available for neutron-scattering, to extract the details of the liquid structure. Although similar measurements have been done before, modern advanced neutron and x-ray-scattering techniques allow collecting the data at much higher resolution and in a wider range of temperatures. Importantly, we were among the first to study fluoride salts by neutron scattering. The importance of impurities and their effects on salt properties have become apparent recently and so new methods of salt purification were developed. We took advantage of these developments to produce reliable data, which have been used for computer simulations of both clean salts and those with added fission and corrosion products most relevant for MSRs. Ab initio molecular dynamics simulations have been performed to understand the multi-component liquid solution, in particular solubility of impurities and thermodynamic interactions in relation to the ionic-cluster structure of the fluid. We applied machine learning to regress from the simulation and experimental data in order to develop a fast-acting model that can handle molten salt with an arbitrary (≥ 10) number of chemical elements and be able to predict chemical potential as a function of composition and temperature. This project resulted in a number of experimental and computer-simulation publications, a patent application, and numerous conference presentations (American Physical Society, American Chemical Society, and The Electrochemical Society among others). Multiple students and postdocs participated and collaborated on aspects of this project. This project seeded new collaborations between MIT and other institutions, such as the University of Massachusetts Lowell, the University of Illinois Urbana-Champaign, the University of California Berkeley, and Oak Ridge and Los Alamos National Labs. As such, this project has had a broad and lasting impact beyond its original scientific scope.
As one of the most potent radioisotopes released during spent nuclear fuel reprocessing, 129 I is strictly regulated and must be removed before discharge. Organic iodides (primarily alkyl iodides with different chain lengths, i.e., CH 3 I, C 4 H 9 I, and C 12 H 25 I) comprise ~2% of the total iodine in the reprocessing off-gases and are primarily present in vessel off-gas (VOG). Reduced silver mordenite (Ag 0 Z) is predominantly considered for the removal of radioiodine; however, its capture performance and underlying interaction processes with long-chain organic iodides are not fully understood. Two major tasks were accomplished in this study. First, to improve upon the previous experimental studies where Ag 0 Z was used to capture CH 3 I, C 4 H 9 I, and C 12 H 25 I at different concentrations, we comprehensively investigated the corresponding capture mechanisms by characterizing fully loaded Ag 0 Z samples. Second, computational codes were implemented to perform fixed-bed simulations that account for transport and reaction mechanisms. Scanning electron microscopy with energy dispersive X-ray analysis (SEM-EDX), powder X-ray diffraction (PXRD), UV-visible diffuse reflectance spectroscopy (UV-vis DRS), and thermogravimetric analysis (TGA) were conducted on Ag 0 Z samples that are saturated with I 2 , CH 3 I, C 4 H 9 I, and C 12 H 25 I), respectively. Results indicate that AgI is the predominant adsorption product regardless of the adsorbed iodine species, yet alkyl iodides with different carbon chain lengths may have different compositions of α- and γ-AgI. Synchrotron pair distribution function (PDF) measurements and TGA coupled with a Fourier transformed infrared detector (TGA FTIR) have been performed, and experimental data are currently analyzed. Results are expected to provide further insights into the adsorption mechanisms. The fixed-bed capture performance for CH 3 I was successfully simulated by solving mathematical equations that describe the underlying transport processes and adsorption reactions. The computational framework, Catalytic After Treatment System (CATS), that was originated in our research group, was used to solve the governing equations. Kinetic parameters, including the pore diffusivity and reaction rate constant were obtained by optimization techniques using data from thin-bed experiments performed at Oak Ridge National Laboratory. The performance of a deep bed predicted using the optimized parameters showed promising agreement with the experimental data.
The United States nuclear industry is facing a strong challenge to ensure maximum safety while enhancing economic benefit. Safety is a key parameter to all aspects related to light water reactor (LWR) nuclear power plants (NPPs), especially cost savings. Since the goal is to extend the lifetimes of these NPPs, the traditional deterministic safety concept may not guarantee a current economic asset. The Light Water Reactor Sustainability (LWRS) Program has been promoting a wide range of research and development (R&D) in this field to maximize the safety, economics, and performance of these NPPs through improved scientific understanding. One of the best practices to achieve this goal is to identify and optimize safety margins, which can lead to cost reduction. To do this, under the LWRS framework, the Risk-Informed Systems Analysis (RISA) Pathway will focus on the optimization of safety margin and minimization of uncertainties to ensure both safety and economics at the highest level. The RISA Pathway will provide enhanced capabilities for analyzing and characterizing LWR systems performance by developing and demonstrating methods, tools, and data to enable risk-informed margins management (RIMM). The goals of the RISA Pathway are twofold: (1) deploy the risk-informed tools and methods that enable better representation of safety margins and factors that contribute to cost and safety; and (2) conduct advanced risk assessment applications with industry to support margin management strategies that enable more cost-effective plant operation. The tools and methods provided by the RISA Pathway will support effective margin management for both active and passive safety systems, structures, and components (SSC) of an NPP. The tools and methods used in the RISA Pathway should have high confidence and highest technical maturity for and implementation to industry at its current setting. They should also have a capability to support risk-informed decision making for both probabilistic and deterministic elements of safety. The RISA Pathway will, therefore, perform a comprehensive assessment of verification and validation (V&V) status of RISA Toolkit to enhance credibility RISA Toolkit which be used by industry. This report summarizes RELAP5-3D development activities for best estimated and uncertainty (BEPU) capability to support ongoing RISA Pathway pilot projects for risk informed uncertainty quantification applications. Work scope includes (1) development of initial perturbation model for selected closure laws and (2) testing of suitable probability distribution functions (PDF) for the selected correlations. Developed BEPU modules are tested with selected separate effect cases and compared with conventional thermal-hydraulics model.
We present results on the nucleon valence quark distribution extracted from Lattice QCD simulations, using a gauge ensemble of Nf=2+1 Wilson-Clover fermions with a pion mass of m?=350 MeV and lattice spacing of a=0.091 fm. We obtain reduced Ioffe Time Distributions (rITDs) by computing appropriate matrix elements on the lattice, and elaborate on the extraction of the desired quark distributions from the rITDs following the pseudo-PDF approach. A set of techniques are considered in order to ensure ground state dominance. Theoretical and experimental implications of our calculation are discussed.
I outline recent developments in lattice QCD that enable the computation of the x-dependent Parton Distribution Functions, and then present recent calculations of the valence PDF of the pion by the HadStruct collaboration. I describe the challenges and opportunities to compute the gluon and sea-quark contributions to meson structure, and how such lattice calculations can form a key part of the physics goals of the EIC.
This project was originally headed by Dr. Abraham Clearfield (Texas A&M University, ret.) and focused on developing structural models of zirconium phosphate (ZrP) based materials at different stages of crystalline order using PDF techniques developed by co-PI Dr. Simon Billinge (Columbia University). When Dr. Clearfield retired, the project was taken over by Dr. Hong-Cai Zhou (Texas A&M University). The project proposed looking at defective metal-organic frameworks (MOFs) supported on the surface of the ZrP materials. During the project, the personnel conducted studies of the dispersion of different phosphate ligands in mixed organic phosphonates, and how they could be utilized to incorporate different metals within the ZrP interlayer spacing.
The overall goal is to improve the performance and economics of existing coal fired power plants by extending low load boiler operation to lower loads than is currently achievable. The objective of this program is to develop and validate sensor hardware and analytical algorithms to lower plant operating expenses (OPEX) for the currently operating pulverized coal utility boiler fleet. Coal fired utility boilers are increasingly under grid dispatch pressure. In some cases, the coal fired cost of generation is noncompetitive with respect to natural gas generation and subsidized renewable sources. To remain profitable and remain fully compliant with existing environmental regulations, the installed coal fired fleet must find technologies which allow it to move into a more flexible cyclic load dispatch model. Today the installed coal fired utility fleet must be cost of generation competitive, fully emissions compliant, and responsive to the variability inherent in renewable energy generation sources. In the Phase I of the project, GE Steam Power, Inc. (GE) performed modeling of different operating scenarios for low load operation using an existing full plant dynamic model developed for a 660MW steam power plant. Sensors and analytic algorithms to enable a stable and steady coal supply for low load pulverizer operation were identified and tested at the Pulverizer Development Facility (PDF) at GE’s Clean Energy Center in Bloomfield, Connecticut. Sensors and analytic algorithms to enable stable combustion for low load operation were identified and tested at the 15 MWth Industrial Scale Burner facility (ISBF) at GE’s Clean Energy Center. A concept was developed to test the sensors and control algorithms, down selected after testing, at a full-scale coal fired power plant. A budget estimate was then developed, and the concept was implemented at an existing utility power plant. The specific objectives of the experimental work were to: • Identify and select sensors and analytic algorithms for monitoring coal pulverizer operation at lower loads to provide stable operation and appropriate coal fineness at lower coal throughput; Identify and select sensors and analytic algorithms for a Boiler Flame Stability Monitor to better balance air and fuel at each burner. This enables a reduction in a coal boiler’s safe low load power level while maintaining stable flame characteristics; Develop a concept in Phase I for low load operation of a full-scale power plant and develop a budget estimate for testing and execute the test plan at an existing plant in Phase II; Validate the capability of the extended low load boiler system to extend the minimum load operating point in a safe and reliable manner on an existing full-scale utility boiler. At the completion of this experimental study, GE has developed a set of sensors and analytic algorithms, down selected after testing, that have the potential to enable safe low load operation of a utility boiler. GE has also identified a host site for testing these identified sensors and analytic algorithms. GE has generated a full set of deliverables that provide sufficient information to proceed with the next step of testing at a host site. This includes a potential host site and budget estimate for concept testing at host site. In the Phase II of the project, a series of field tests were completed to validate the extended low load boiler operation, which consisted of detailed engineering, installation, commissioning, and testing the additional sensors and analytics for the coal-fired combustion system on an existing full-scale utility boiler. The optimization work has been supported by the host plant and endorsed by their engineering and operation staff.
I discuss basic principles and results of pseudo-PDF approach to extraction of parton distributions from the lattice.
This presentation finds that defining the marginal probability density function (PDF) for nuclear data is important. Additionally, the vocabulary of “means and covariances” and new GNDS 2.0 formats are limited to Gaussian (normal) representations— always incorrect—but clearly of practical significance when uncertainties are large (>40%). Finally, the Triage Solution: declare our current data as containing best estimate (mode) plus variance for a truncated normal or lognormal.
The slides are screenshots of a project created with the Ignition software platform by Inductive Automation for the Short-Baseline Near Detector (SBND). They depict the human-machine interface (HMI) for the experiment’s cryogenic system. As the HMI itself is not of a format that may be converted to PDF or similar document, these slides present a comprehensive set of screenshots of all windows within the HMI that may be publicly presented.
The ASCII MCNP output file is converted to an interactive PDF using legacy printer control characters.
This newsletter, published quarterly, features LDRD and SDRD work done by Lawrence Livermore, Los Alamos, Nevada National Security Site and Sandia. To see a PDF with all articles referenced in this newsletter or review past issues, visit NNSA-LDRD.lanl.gov and click on the Quarterly Highlights tab.
The Justice Underpinning Science and Technology Research (JUST-R) Metrics Framework is a set of metrics for assessing the energy justice implications of technologies that are currently under research and development (R&D). The JUST-R Metrics Framework guides researchers through an analysis of the many facets of their research processes, from material inputs to knowledge sources, that may contribute to energy injustice both during the research period and when the technology is scaled. This JUST-R Offline Tool consists of an Excel file and PDF guide to aid researchers, engineers, and project managers in their application of the JUST-R Metrics Framework. This tool enables researchers to 1) evaluate the baseline energy justice implications of their research; 2) develop justice-oriented changes to the research process; and 3) track the implementation of proposed changes. The metrics included in the framework are sorted into five aspects of research: Team Dynamics, Sources & Inputs, Processes & Protocols, Waste & Hazards, and Results & Dissemination. The JUST-R Tool can be found here: https://www.nrel.gov/analysis/just-r.html.
Within the pseudo-PDF framework, we investigate the perturbative contributions to correlators that are used to study transverse momentum dependent parton distributions (TMDs) on the lattice. Our results contain the full perturbative corrections which arise as artifacts from performing the calculation for a Euclidean separation between the parton fields, as well as the corrections which yield the evolution equations for the TMDs. This gives a path to extraction of the genuine non-perturbative features of the three-dimensional structure of the hadrons from lattice calculations.
HIV Molecular Immunology is a companion volume to HIV Sequence Compendium. This publication, the 2025 edition, is the PDF version of Los Alamos Na tional Laboratory’s web-based HIV Molecular Immunology Database (https://www.hiv.lanl.gov/content/ immunology/). The web interface for this relational database has many search interfaces for HIV immunological in formation, as well as interactive tools to help immunologists design reagents and interpret their results.
MCFM is a dedicated Monte-Carlo simulation program for collider phenomenology at highest energies. Designed during the Tevatron era, it has successfully incorporated the latest developments needed for LHC precision calculations and remained on the forefront of collider phenomenology. The Fortran code includes interfaces to modern PDF and loop reduction libraries but has been unchanged structurally compared to the earlier versions. Parallel computing has been enabled using OpenMP and MPI. MCFM provides numerically highly stable one-loop amplitudes and superior phase-space efficiency, leading to excellent performance in NXLO calculations using jettiness or qT subtraction techniques for IR regularization.
This dataset contains 1,261 hydropower facilities with associated Federal Energy Regulatory Commission (FERC) relicensing metrics. Anticipated FERC license renewal dates are summarized by river reach for observing areas of opportunities for basin-wide collaboration on environmental mitigations. Identifying rivers and basins with facilities that have similar anticipated Federal Energy Regulatory Commission (FERC) relicensing dates may be one potential indicator that multiple licensees within the same basin may be willing to collaborate on a basin-scale relicensing effort. The hydropower relicensing process requires long-term resource allocation by agencies, hydropower owner/operators, non-governmental organizations, and tribal, state, and federal governments. Basin-scale hydropower relicensing has begun to receive attention as a potential solution for reducing licensing timelines, costs, and uncertainty which can provide benefits to a broad spectrum of participants in the licensing process. This dataset contains one a data file in comma separated (*.csv) format, a data dictionary in *.csv format, and a user guide in *.pdf format. These data are also available as an interactive web map available at: