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DOE OSTI2014

Radiation protection at the SwissFEL free electron laser facility: Beam stopping devices - Paper 53

The new large-scale facility SwissFEL (Swiss Free Electron Laser) is currently under construction at the Paul Scherrer Institute. The facility is situated underground in the ground floor of a two-floor building, partly integrated in a recreation area. This results into new challenges for radiation protection related tasks, in particular for the design of beam-stopping devices. The design of each beam-stopping device has to ensure that the dose rate during operation outside of the accelerator vault is in compliance with the legal limits defined by the Swiss radiation protection ordinance. In this work, the final design of the dumps is presented with the description of the underlying operational and legal constraints. Reuse of activated material as concrete, lead and steel is included in the main design criteria. As a result, four beam stopping devices consist for more than 90 % of material already available at PSI. In addition, routine operation and maintenance scenarios are discussed from a radiation protection point of view. (authors)

42 ENGINEERING↗

DOE OSTI2024

2024 JISEA Annual Meeting: Session 1

This is the presentation for the 2024 JISEA Annual Meeting Session 1: Hard-to-Decarbonize Industries, which took place on February 26, 2024. The presentation includes slides from Chad Reese, Environmental Affairs Manager at the San Diego County Regional Airport Authority, on sustainability efforts at the San Diego International Airport; Jordan Lambert, Director of Ag Innovation at Colorado State University, on agricultural decarbonization; Ana Aday, Materials Science Researcher at NREL, on decarbonizing the cement and concrete industry; and Rolf Weberg, Director of the Natural Resource Research Institute at the University of Minnesota Duluth, on integrated industrial decarbonization.

agriculture decarbonization↗

DOE OSTI2025

Integrating Crack Detection and Pipe Shape Optimization for Enhanced Sewage System Durability

Crack detection in underground reinforced concrete pipes has been essential in determining the state of stormwater infrastructure. Detection models have been implemented for detecting cracks and other defects in pipes using CCTV footage for stormwater drainage systems. In addition, Finite element models have been used to determine optimum shapes and pipe thickness for different boundary conditions such as header pipes in power plants. The concept of shape optimization emerges as a crucial factor in power plant design and operation, with the potential to maximize performance while minimizing the use of materials. Shape optimization not only enhances efficiency but also contributes to reducing the environmental footprint. This paper discusses the integration of both topics by using the cracks detected in underground pipes as boundary conditions for shape optimization of the pipes. A machine learning model has been developed which uses limited data for training and outlines the location of detected cracks. A shape optimization methodology is proposed in which ANSYS modules are used to analyze fluid flow and then optimize the shape of the pipe. The crack detection model developed has been applied to a crack detected in lab setting and machine learning model used has an accuracy of 98% using a random forest algorithm.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2018

Design for Highly Piezoelectric and Visible/Near-Infrared Photoresponsive Perovskite Oxides

Defect–engineered perovskite oxides that exhibit ferroelectric and photovoltaic properties are promising multifunctional materials. Though introducing gap states by transition metal doping on the perovskite B–site can obtain low bandgap (i.e., 1.1–3.8 eV), the electrically leaky perovskite oxides generally lose piezoelectricity mainly due to oxygen vacancies. Therefore, the development of highly piezoelectric ferroelectric semiconductor remains challenging. Here, inspired by point–defect–mediated large piezoelectricity in ferroelectrics especially at the morphotropic phase boundary (MPB) region, an efficient strategy is proposed by judiciously introducing the gap states at the MPB where defect–induced local polar heterogeneities are thermodynamically coupled with the host polarization to simultaneously achieve high piezoelectricity and low bandgap. A concrete example, Ni 2+ –mediated (1– x )Na 0.5 Bi 0.5 TiO 3– x Ba(Ti 0.5 Ni 0.5 )O 3–δ ( x = 0.02–0.08) composition is presented, which can show excellent piezoelectricity and unprecedented visible/near–infrared light absorption with a lowest ever bandgap ≈0.9 eV at room temperature. In particular, the MPB composition x = 0.05 shows the best ferroelectricity/piezoelectricity ( d 33 = 151 pC N –1 , P r = 31.2 μC cm –2 ) and a largely enhanced photocurrent density approximately two orders of magnitude higher compared with classic ferroelectric (Pb,La)(Zr,Ti)O 3 . Furthermore, this research provides a new paradigm for designing highly piezoelectric and visible/near–infrared photoresponsive perovskite oxides for solar energy conversion, near–infrared detection, and other multifunctional applications.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Strong Rashba-Dresselhaus Effect in Nonchiral 2D Ruddlesden-Popper Perovskites

Chirality transfer from organic chiral molecules to lead halides is theorized as the origin of the strong Rashba-Dresselhaus effect causing large circular dichroism (CD) and circularly polarized luminescence (CPL) in metal halide perovskites (MHPs). In this report a concrete empirical evidence is provided that such strong CD and CPL can occur even in nonchiral 2D Ruddlesden-Popper perovskites (RPPs) (BA) 2 (MA) n-1 Pb n I 3n+1 (where MA = CH 3 NH 3 and BA = CH 3 (CH 2 ) 3 NH 3 ). The CD and CPL responses occurring at the excitonic transition of the MHPs are strongest (≈100 mdeg and 4.8%, respectively) when a single lead halide octahedral [PbI 6 ] 4- layer is repeatedly stacked between two nonchiral molecules BA + (n = 1). However, they are rapidly quenched as n increases. It is hypothesized that strong Rashba-Dresselhaus splitting in the 2D RPPs originates the strong CD and CPL signatures. Density functional theory calculations reveal that the large interlayer distortions in the inorganic layers at the organic/inorganic interface give rise to the strong Rashba-Dresselhaus splitting. A Rashba-Dresselhaus field of ≈600 and ≈50 mT for n = 1 and 2, respectively, is estimated by magnetic circular dichroism spectroscopy. The studies may have significant impact on designing 2D RPPs with large Rashba-Dresselhaus effects at room temperature for spintronic applications.

circular dichroism↗

DOE OSTI2020

Quantifying Losses and Assessing the Photovoltage Limits in Metal–Insulator–Semiconductor Water Splitting Systems

Metal–insulator–semiconductor (MIS) photo-electrocatalysts offer a pathway to stable and efficient solar water splitting. Initially motivated as a strategy to protect the underlying semiconductor photoabsorber from harsh operating conditions, the thickness of the insulator layer in MIS systems has recently been shown to be a critical design parameter which can be tuned to optimize the photovoltage. Here we analyze the underlying mechanism by which the thickness of the insulator layer impacts the performance of MIS photo-electrocatalysts. A concrete example of an Ir/HfO 2 /n-Si MIS system is investigated for the oxygen evolution reaction. The results of combined experiments and modeling suggest that the insulator thickness affects the photovoltage i) favorably by controlling the flux of charge carriers from the semiconductor to the metal electrocatalyst and ii) adversely by introducing nonidealities such as surface defect states which limit the generated photovoltage. It is important to quantify these different mechanisms and suggest avenues for addressing these nonidealities to enable the rational design of MIS systems that can approach the fundamental photovoltage limits. The analysis described in this contribution as well as the strategy toward optimizing the photovoltage are generalizable to other MIS systems.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Experimental validation of multiphysics model simulations of the thermal response of a cement clinker rotary kiln at laboratory scale

Abstract An increasing demand for buildings, transportation systems and civil infrastructure development has driven expansion of cement consumption world‐wide, producing a significant increase in related global energy demand. With approximately 7% of the world‐wide industrial energy consumption (10.7 exajoules [EJ]), the cement industry is the third most energy intensive industrial processes and a key component for concrete, the most consumed composite material in the global construction industry. In cement manufacturing, the cement kiln accounts for most of the energy consumption in the production process. As the heart of a cement plant, the cement kiln is where the kiln feed primarily containing calcium oxide (CaO), silica (SiO 2 ), alumina (Al 2 O 3 ), and iron (Fe 2 O 3 ) are thermally and chemically transformed into clinker minerals. The presented work developed a multiphysics model, designed and built a laboratory‐scale rotary cement clinker kiln, and produced cement clinker at laboratory‐scale. The model was developed to study the interaction between the various thermal, fluid dynamic and chemical interactions involved in the sintering process used to form Portland cement clinker in an effort to reduce energy use. The analytical model was validated through experimental testing using a unique laboratory‐scale rotary cement kiln developed during the investigation. Also demonstrated was the feasibility of producing clinker at laboratory scale. This modeling and lab scale tests were designed to better understand the clinker sintering process so that operational and quality decisions can be made to optimize energy consumption without compromising cement clinker quality. The computational fluid dynamics modeling was developed in COMSOL Multiphysics 6.0. The characteristics of the combustion fluid flow, concentration of species, temperature and heat transfer were studied for a turbulent flow of methane (CH 4 ) gas and oxygen (O 2 ). Theory suggests that heat transfer impacts the cement production process but the multiphysics model more accurately describes the convection, conduction, and radiant heat transfer in the kilning process and thus allows for a better understanding of the energy exchange driving the chemical reactions that produce Portland cement. Clinker minerals were formed because of appropriate burning conditions implemented during experimental model validation.

Tabares, Juan David↗

DOE OSTI2022

A machine learning approach for clinker quality prediction and nonlinear model predictive control design for a rotary cement kiln

Abstract Cement manufacturing is energy‐intensive (5Gj/t) and comprises a significant portion of the energy footprint of concrete systems. Incorporating modern monitoring, simulation and control systems will allow lower energy use, lower environmental impact, and lower costs of this widely used construction material. One of the goals of the CESMII roadmap project on the Smart Manufacturing of Cement included developing an analytical process model for clinker quality that includes the chemistry of the kiln feed and accounts for critical process variables. This predictive model will be used in nonlinear model predictive control system designed to significantly reduce process energy use while maintaining or improving product quality. In the cement manufacturing plant used in this study, the kiln feed (meal) is tested every 12 h and used to estimate the mineral composition of the cement kiln output (clinker) using the stoichiometry‐based Bogue's model and the expertise of the plant operators. During kiln operation, kiln output (clinker) is sampled and tested every 2 h to measure its chemical and mineral composition. The predicted and measured values of the clinker composition are used by the plant operators to adjust the kiln input stream and the production process characteristics to maintain stable operation and uniform product quality. However, the time delay between prediction and testing, along with inaccuracies inherent in the Bogue's model have made any process changes designed to minimize energy use problematic, especially in‐light of potential clinker quality issues that process changes often pose. A new analytical model that integrates quality information and process operation information has been developed from data collected from 2 years of production from an operating cement facility. To make the model fuel‐type‐independent, consumed heat energy was computed in the model instead of fuel type and amount. A Feedforward Network was trained and tailored from collected data. Many data‐based simulations were conducted to quantitatively evaluate the proposed model and the 5‐fold cross‐validation procedure was used to test the models. The resulting predictive model was shown to have a low root mean square error (MSE) with respect to the estimated clinker mineral composition compared to that using the industry standard “Bogue’ model”. The end goal of this work was to develop a single machine learning tool that allows the use of quality control data and process control variables to improve energy efficiency of the process in a continuous fashion. The proposed nonlinear model predictive control system (NMPC) can generate predicted kiln production characteristics based on manipulated variables in manner that accurately follows the target product quality values. Simulation results also show that the proposed model produced accurate predictions of kiln outputs that fell within the required constraints, while manipulating control variables within typical operational ranges.

Ali, Asem M.↗

DOE OSTI2025

BRE‐X Emissions Database for End‐of‐Life Scenarios of Selective Building Construction Materials to Enable Circular Economy in Construction

In the United States, construction and demolition debris predominately end up in landfills with minimal end‐of‐life Re‐X (recover, recycle, reuse, etc.) scenarios, resulting in large environmental impacts and lost opportunities for material recovery. Except for concrete and metals, which seem to have a few well‐defined end‐of‐life pathways, there seems to be a lack of well‐documented end‐of‐life scenarios for other construction materials, let alone their emissions data. Hence, there is a need for documented end‐of‐life Re‐X scenarios and end‐of‐life data of more building materials to motivate widespread use of Re‐X strategies in building design. This paper outlines the efforts of the National Renewable Energy Laboratory, Carbon Leadership Forum, Building Transparency, and Skidmore, Owings & Merrill to (a) create an open‐access BRE‐X (Building Re‐X) end‐of‐life emissions database consisting of greenhouse gas emissions data associated with various end‐of‐life scenarios for a select list of high‐impact building construction materials, and (b) integrate the BRE‐X end‐of‐life emissions database with CAD/BIM/LCA tools for evaluating various end‐of‐life scenarios. The paper also presents a few existing life cycle inventory databases that contain sparse amounts of end‐of‐life data for a few construction materials and their limitations in terms of scaling and data consolidation. Finally, a sample of how the collected data can be ingested into whole‐building LCA tools using open data formats and a public access link to the BRE‐X end‐of‐life emissions database is also included.

36 MATERIALS SCIENCE↗

DOE OSTI2019

Influence of Van der Waals Interactions on the Solvation Energies of Adsorbates at Pt-Based Electrocatalysts

Solvation can significantly modify the adsorption energy of species at surfaces, thereby influencing the performance of electrocatalysts and liquid-phase catalysts. Thus, it is important to understand adsorbate solvation at the nanoscale. Here we evaluate the effect of van der Waals (vdW) interactions described by different approaches on the solvation energy of *OH adsorbed on near-surface alloys (NSAs) of Pt. Our results show that the studied functionals can be divided into two groups, each with rather similar average *OH solvation energies: (1) PBE and PW91; and (2) vdW functionals, RPBE, PBE-D3 and RPBE-D3. On average, *OH solvation energies are less negative by ~0.14 eV in group (2) compared to (1), and the values for a given alloy can be extrapolated from one functional to another within the same group. Depending on the desired level of accuracy, these concrete observations and our tabulated values can be used to rapidly incorporate solvation into models for electrocatalysis and liquid-phase catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2019

The AQUA-MER databases and aqueous speciation server: A web resource for multiscale modeling of mercury speciation

To assess the chemical reactivity, toxicity, and mobility of pollutants in the environment, knowledge of their species distributions is critical. Because their direct measurement is often infeasible, speciation modeling is widely adopted. Mercury (Hg) is a representative pollutant for which study of its speciation benefits from modeling. However, Hg speciation modeling is often hindered by a lack of reliable thermodynamic constants. Although computational chemistry (e.g., density functional theory [DFT]) can generate these constants, methods for directly coupling DFT and speciation modeling are not available. Here, we combine computational chemistry and continuum-scale modeling with curated online databases to ameliorate the problem of unreliable inputs to Hg speciation modeling. Our AQUA-MER databases and web server (https://aquamer.ornl.gov) provides direct speciation results by combining web-based interfaces to a speciation calculator, databases of thermodynamic constants, and a computational chemistry toolkit to estimate missing constants. Lastly, although Hg is presented as a concrete use case, AQUA-MER can also be readily applied to other elements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Positive Co‐Degree Density of Hypergraphs

The minimum positive co-degree of a nonempty r-graph H, denoted $δ^+_{r-1}$ (H), is the maximum k such that if S is an (r-1)-set contained in a hyperedge of H, then is contained in at least distinct hyperedges of H. Given an r-graph F, we introduce the positive co-degree Turán number co + ex(n, F) as the maximum positive co-degree $δ^+_{r-1}$ (H) over all n-vertex r-graphs H that do not contain F as a subhypergraph. In this paper, we concentrate on the behavior of co + ex(n, F) for 3-graphs F. In particular, we determine asymptotics and bounds for several well-known concrete 3-graphs F (e.g. $K^-_4$ and the Fano plane). Here, we also show that, for r-graphs, the limit γ + (F)≔ lim$_{n→∞}$ $\frac{co^+ex(n, F)}{n}$ exists, and “jumps” from 0 to 1/r, that is, it never takes on values in the interval . Moreover, we characterize which r-graphs F have γ + (F) = 0. Our motivation comes primarily from the study of (ordinary) co-degree Turán numbers where a number of results have been proved that inspire our results.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Multiscale plasticity of geomaterials predicted via constrained optimization‐based granular micromechanics

Abstract A general framework to derive nonlinear elastic and elastoplastic material models from granular micromechanics is proposed, where a constraint‐based variational structure is introduced to classical grain contact‐based homogenization methods of hyperelasticity. Like the classical hyperelastic methods, reference solutions for closed‐form hyperelastic material models are analytically derived from the grain‐scale contact mechanics. However, unlike prior methods, the proposed homogenization framework defines closed‐form hyperelastoplastic material models that extend multiscale variational methods to granular plasticity. The proposed framework is used to develop novel granular micromechanics‐based macroscopic models for a Mises type solid, Drucker–Prager type plasticity, and grain‐contact cohesive‐debonding with a deviatorically and volumetrically coupled nonlinearly elastic response. Macroscopic plastic parameters and yield criteria are explicitly related to their microscale counterparts, for example, the friction coefficient governing intergranular slip. Numerical examples and comparison to measurements from the literature, including triaxial compaction of concrete, are provided to investigate model predictions and demonstrate calibration to experimental data.

Bryant, E. C.↗

DOE OSTI2019

Nonlinear Resonant Ultrasound Spectroscopy for Predicting Sensitivity to Initiation in Granular High Explosives

Abstract Nonlinear Resonant Ultrasound Spectroscopy (NRUS) is a technique that can measure bulk nonlinear coefficients of the nonlinear elastic modulus for a material. NRUS has been used to identify damage in a variety of granular materials including rocks and concrete. Some energetic materials, such as Pentaerythritol Tetranitrate (PETN), are commonly fielded as pressed granular compacts. It is well known that the sensitivity to initiation of these materials is heavily dependent on their microstructure, and that microstructure changes naturally (becomes damaged) over time. In this study, we examine the use of NRUS to identify changes in microstructure between pristine and thermally aged PETN pellets. In particular, we examine the relationship between the bulk hysteretic nonlinearity, α , of the pellets and time spent at temperature, powder specific surface area (SSA), and sensitivity to initiation. We find that, in general, α does not increase uniformly for all pellets within a single thermal aging condition. However, when the pellets are test fired to determine sensitivity to initiation, there is a strong correlation between α and firing voltage threshold. NRUS‐measured α has the added benefit that the measurements can be made in situ and on benchtop scales.

Schulze, Peter↗

DOE OSTI2019

Domain-specific virtual processors as a portable programming and execution model for parallel computational workloads on modern heterogeneous high-performance computing architectures

We advocate domain-specific virtual processors (DSVP) as a portability layer for expressing and executing domain-specific computational workloads on modern heterogeneous HPC architectures, with applications in quantum chemistry. Specifically, in this article we extend, generalize and better formalize the concept of a domain-specific virtual processor as applied to scientific high-performance computing. In particular, we introduce a system-wide recursive (hierarchical) hardware encapsulation mechanism into the DSVP architecture and specify a concrete microarchitectural design of an abstract DSVP from which specialized DSVP implementations can be derived for specific scientific domains. Furthermore, we demonstrate, an example of a domain-specific virtual processor specialized to numerical tensor algebra workloads, which is implemented in the ExaTENSOR library developed by the author with a primary focus on the quantum many-body computational workloads on large-scale GPU-accelerated HPC platforms.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Jay : A software framework for prototyping and evaluating offloading applications in hybrid edge clouds

Abstract We present Jay , a software framework for offloading applications in hybrid edge clouds. Jay provides an API, services, and tools that enable mobile application developers to implement, instrument, and evaluate offloading applications using configurable cloud topologies, offloading strategies, and job types. We start by presenting Jay 's job model and the concrete architecture of the framework. We then present the programming API with several examples of customization. Then, we turn to the description of the internal implementation of Jay instances and their components. Finally, we describe the Jay Workbench, a tool that allows the setup, execution, and reproduction of experiments with networks of hosts with different resource capabilities organized with specific topologies. The complete source code for the framework and workbench is provided in a GitHub repository.

Silva, Joaquim↗

DOE OSTI2022

Transitioning from File-Based HPC Workflows to Streaming Data Pipelines with openPMD and ADIOS2

This paper aims to create a transition path from file-based IO to streaming-based workflows for scientific applications in an HPC environment. By using the openPMP-api, traditional workflows limited by filesystem bottlenecks can be overcome and flexibly extended for in situ analysis. The openPMD-api is a library for the description of scientific data according to the Open Standard for Particle-Mesh Data (openPMD). Its approach towards recent challenges posed by hardware heterogeneity lies in the decoupling of data description in domain sciences, such as plasma physics simulations, from concrete implementations in hardware and IO. The streaming backend is provided by the ADIOS2 framework, developed at Oak Ridge National Laboratory. This paper surveys two openPMD-based loosely-coupled setups to demonstrate flexible applicability and to evaluate performance. In loose coupling, as opposed to tight coupling, two (or more) applications are executed separately, e.g. in individual MPI contexts, yet cooperate by exchanging data. This way, a streaming-based workflow allows for standalone codes instead of tightly-coupled plugins, using a unified streaming-aware API and leveraging high-speed communication infrastructure available in modern compute clusters for massive data exchange. We determine new challenges in resource allocation and in the need of strategies for a flexible data distribution, demonstrating their influence on efficiency and scaling on the Summit compute system. The presented setups show the potential for a more flexible use of compute resources brought by streaming IO as well as the ability to increase throughput by avoiding filesystem bottlenecks.

Poeschel, Franz↗

DOE OSTI2015

Soft collinear effective theory for heavy WIMP annihilation

In a large class of models for Weakly Interacting Massive Particles (WIMPs), the WIMP mass M lies far above the weak scale m W . This work identifies universal Sudakov-type logarithms ~ α log 2 (2 M/m W ) that spoil the naive convergence of perturbation theory for annihilation processes. An effective field theory (EFT) framework is presented, allowing the systematic resummation of these logarithms. Another impact of the large separation of scales is that a long-distance wavefunction distortion from electroweak boson exchange leads to observable modifications of the cross section. Careful accounting of momentum regions in the EFT allows the rigorous disentanglement of this so-called Sommerfeld enhancement from the short-distance hard annihilation process. In addition, the WIMP is described as a heavy-particle field, while the electroweak gauge bosons are treated as soft and collinear fields. Hard matching coefficients are computed at renormalization scale μ ~ 2 M , then evolved down to μ ~ m W , where electroweak symmetry breaking is incorporated and the matching onto the relevant quantum mechanical Hamiltonian is performed. The example of an SU(2) W triplet scalar dark matter candidate annihilating to line photons is used for concreteness, allowing the numerical exploration of the impact of next-to-leading order corrections and log resummation. As a result, for M ≃ 3 TeV, the resummed Sommerfeld enhanced cross section is reduced by a factor of ~ 3 with respect to the treelevel fixed order result.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗