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DOE OSTI2023

SeeQ: A Programming Model for Portable Data-Driven Building Applications

This paper introduces SeeQ, a programming model and an abstraction framework that facilitates the development of portable data- driven building applications. Data-driven approaches can provide insights into building operations and guide decision-making to achieve operational objectives. Yet the configuration of such applications per building requires extensive effort and tacit knowledge. In SeeQ, we propose a portable programming model and build a software system that enables self-configuration and execution across diverse buildings. The configuration of each building is captured in a unified data model - in this paper, we work with the Brick ontology without loss of generality. SeeQ focuses on the distinction between the application logic and the configuration of an application against building-specific data inputs and systems. We test the proposed approach by configuring and deploying a diverse range of applications across five heterogeneous real-world buildings. The analysis shows the potential of SeeQ to significantly reduce the efforts associated with the delivery of building analytics.

analytics↗

DOE OSTI2022

LBNL Fault Detection and Diagnostics Datasets

These datasets can be used to evaluate and benchmark the performance accuracy of Fault Detection and Diagnostics (FDD) algorithms or tools. It contains operational data from simulation, laboratory experiments, and field measurements from real buildings for seven HVAC systems/equipment (rooftop unit, single-duct air handler unit, dual-duct air handler unit, variable air volume box, fan coil unit, chiller plant, and boiler plant). Each dataset includes a .pdf file to document key information necessary to understand the content and scope, multiple csv files containing all the time-series data for faults at different severity levels and one fault-free case, and a ttl file to visualize the data according to BRICK schema. The dataset was created by LBNL, PNNL, NREL, ORNL and Drexel University.

AC↗

DOE OSTI2021

Development and Application of Schema Based Occupant-Centric Building Performance Metrics

Occupant behavior can significantly influence the operation and performance of buildings. Many occupant-centric key performance indicators (KPIs) rely on having accurate counts of the number of occupants in a building, which is very different to how occupancy information is currently collected in the majority of buildings today. To address this gap, the authors develop a standardized methodology for the calculation of percent space utilization for buildings, which is formulated with respect to two prevalent operational data schemas: the Brick Schema and Project Haystack. The methodology is scalable across different levels of spatial granularity and irrespective of sensor placement. Moreover, the methods are intended to make use of typical occupancy sensors that capture presence level occupancy and not counts of people. Since occupant-hours is a preferable metric to use in KPI calculations, a method to convert between percent space utilization and occupant-hours using the design occupancy for a space is also developed. The methodology is demonstrated on a small commercial office space in Boulder, Colorado using data collected between June 2018 and February 2019. A multiple linear regression is performed that shows strong evidence for a relationship between building energy consumption and percent space utilization.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

Wash Penalty Factors: Insight into the Effects of Water Wash Down of Building Materials for Radionuclide/Nuclear (Rn) Decontamination - 20153

The release of radiological material to the urban environment can have a devastating socio-economic impact. In an urban release scenario, areas around the dispersal epicenter and any areas contaminated via atmospheric deposition may require extensive decontamination. Most recently, our group reported the decontamination efficacy of pressurized water washing of common porous building materials, and compared the penetration depth of the contaminations before and after exposure to pressurized tap water. Here, we continue evaluation of the decontamination efficacy of wash solutions based on potassium (K{sup +}) salt for cesium (Cs), strontium (Sr), and europium (Eu) contaminations on common building surfaces. The surfaces included: the cement used in concrete, the aggregate used in concrete, intact concrete, roadway asphalt, asphalt shingles, and latex paint. We deposited solutions of {sup 137}Cs, {sup 85}Sr, and {sup 152}Eu onto numerous common building materials and exposed these materials to a static bath or low-pressure flow of tap water, 0.1 M potassium chloride (KCl), and 0.5 M KCl. The decontamination efficacy and the depth profile for residual contamination were measured to determine the conditions under which applying a wash solution has benefit compared to physically removing the surface material. To aid in these analyses, we introduced a 'wash penalty factor' to quantify the degree to which contamination migrated into the bulk material by the action of the wash method. On asphalt, 70-80% of the radionuclides were found to be within 0.02 mm of the surface. Cs{sup +} bonded to negative charge sites on the surface of the mineral aggregate (used in concrete) so decontamination was improved by ion exchange with K{sup +}. Sr{sup 2+} is soluble and removed by water, while not bonding to aggregate or demonstrating solubility in the liquid asphalt. Eu{sup 3+} is precipitated and not removed in gentle wash but displays mobility within the pore space that suggests its presence as a colloid. Concrete is more porous than asphalt, and 80% of the radionuclides were within 0.2 mm of the surface for {sup 137}Cs and {sup 152}Eu and 50- 80% for {sup 85}Sr. On concrete, Cs{sup +} bonds similarly to asphalt. Sr{sup 2+} bonds to the cement or precipitates from the alkaline pore water. Eu{sup 3+} sorbs to the cement and then precipitates. In brick, the results for Cs{sup +} and Sr{sup 2+} suggested that diffusion of ions from deeper in the coupon was important. Eu{sup 3+} is removed poorly due to precipitation. We will explain and report example wash penalty factors that vary from 0 to > 1 for the various methods and the implications for deciding when to implement wash down methods. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2021

Two‐Dimensional (2D) or Quasi‐2D Superstructures from DNA‐Coated Colloidal Particles

Abstract This contribution describes the synthesis of colloidal di‐patch particles functionalized with DNA on the patches and their assembly into colloidal superstructures via cooperative depletion and DNA‐mediated interactions. The assembly into flower‐like Kagome, brick‐wall like monolayer, orthogonal packed single or double layers, wrinkled monolayer, and colloidal honeycomb superstructures can be controlled by tuning the particles’ patch sizes and assembly conditions. Based on these experimental results, we generate an empirical phase diagram. The principles revealed by the phase diagram provide guidance in the design of two‐dimensional (2D) materials with desired superstructures. Our strategy might be translatable to the assembly of three‐dimensional (3D) colloidal structures.

Liu, Mingzhu↗

DOE OSTI2021

Two‐Dimensional (2D) or Quasi‐2D Superstructures from DNA‐Coated Colloidal Particles

Liu, Mingzhu↗

DOE OSTI2020

“Lagrangian disks” in M-theory

While the study of bordered (pseudo-)holomorphic curves with boundary on Lagrangian submanifolds has a long history, a similar problem that involves (special) Lagrangian submanifolds with boundary on complex surfaces appears to be largely overlooked in both physics and math literature. We relate this problem to geometry of coassociative submanifolds in G 2 holonomy spaces and to Spin(7) metrics on 8-manifolds with T 2 fibrations. As an application to physics, we propose a large class of brane models in type IIA string theory that generalize brane brick models on the one hand and 2d theories T[M 4 ] on the other.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2022

Evading strength and ductility trade-off in an inverse nacre structured magnesium matrix nanocomposite

Mimicking nacre structure is an often-used strategy for developing materials which combine high strength and high toughness. Here, a novel strategy, named inverse nacre structure, is proposed where elongated and curled soft constituents are embedded in a matrix of hard constituent to form an ordered brick-and-mortar arrangement. This strategy is demonstrated in a particle reinforced metal matrix composite, using pure Mg as the soft phase and SiC nanoparticle reinforced Mg as the hard phase. In this work, the resulting nanocomposite yields high strength, and especially high tensile elongation which is five times that of the homogeneous counterpart. The superior comprehensive strengthening-toughening effect originates from the tailored inverse nacre structure which enables a stable microcrack-multiplication process by sufficiently promoting strain hardening so as to avoid any significant decrease in post-ultimate tensile strength. This strategy, while demonstrated here for the specific case of particle reinforced Mg, is not restricted to any particular material system but constitutes a generic pathway for the development of high-performance materials for engineering applications.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Effect of magneto-mechanical synergism in the process-structure correlation in Fe–C alloys: A phase-field modeling approach

Applied magnetic fields can alter phase equilibria and kinetics in steels; however, quantitatively resolving how magnetic, chemical, and elastic driving forces jointly influence the microstructure remains challenging. We develop a quantitative magneto-mechanically coupled phase-field model for the Fe–C system that couples a CALPHAD-based chemical free energy with demagnetization-field magnetostatics and microelasticity. Here, the model reproduces single- and multi-particle evolution during the α → γ inverse transformation at 1023 K under external fields up to 20 T, including ellipsoidal morphologies observed experimentally at 8 T. Chemically driven growth is isotropic; a magnetic interaction introduces an anisotropic driving force that elongates γ precipitates along the field into ellipsoids, while elastic coherency promotes faceting, yielding elongated cuboidal or “brick-like” particles under combined magneto-elastic coupling. Growth kinetics increase with C content, and decrease with field strength and misfit strain. Multi-particle simulations reveal dipolar interaction-mediated coalescence for field-parallel neighbors and ripening for field-perpendicular neighbors. Incorporating field-dependent diffusivity from experiment slows kinetics as expected; a first-principles-motivated anisotropic diffusivity correction is estimated to be small (<2%). These results establish a process-structure link for magnetically assisted heat treatments of Fe–C alloys and provide guidance for microstructure control via chemo-magneto-mechanical synergism.

Magnetic field↗

DOE OSTI2020

Unified architecture for data-driven metadata tagging of building automation systems

This article presents a Unified Architecture (UA) for automated point tagging of Building Automation System (BAS) data, based on a combination of data-driven approaches. Advanced energy analytics applications—including fault detection and diagnostics and supervisory control—have emerged as a significant opportunity for improving the performance of our built environment. Effective application of these analytics depends on harnessing structured data from the various building control and monitoring systems, but typical BAS implementations do not employ any standardized metadata schema. While standards such as Project Haystack and Brick Schema have been developed to address this issue, the process of structuring the data, i.e., tagging the points to apply a standard metadata schema, has, to date, been a manual process. This process is typically costly, labor-intensive, and error-prone. In this work we address this gap by proposing a UA that automates the process of point tagging by leveraging the data accessible through connection to the BAS, including time-series data and the raw point names. The UA intertwines supervised classification and unsupervised clustering techniques from machine learning and leverages both their deterministic and probabilistic outputs to inform the point tagging process. Furthermore, we extend the UA to embed additional input and output data-processing modules that are designed to address the challenges associated with the real-time deployment of this automation solution. We test the UA on two datasets for real-life buildings: (i) commercial retail buildings and (ii) office buildings from the National Renewable Energy Laboratory (NREL) campus. We report the proposed methodology correctly applied 85–90% and 70–75% of the tags in each of these test scenarios, respectively for two significantly different building types used for testing UA's fully-functional prototype. The proposed UA, therefore, offers promising approach for automatically tagging BAS data as it reaches close to 90% accuracy. Further building upon this framework to algorithmically identify the equipment type and their relationships is an apt future research direction to pursue.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

Excessive radon-based radiation in indoor air caused by soil building materials in traditional homes on Đồng Văn karst plateau, northern Vietnam

Radon-based radiation from natural soil building materials is an important factor likely influencing residents’ health as a contributing source of natural radiation. This work aims to quantify the nuclide-specific α-radiation of isotopes 222 Rn and 220 Rn in common types of houses in a region of northern Vietnam, Ɖông Văn karst plateau, to preliminarily (i) evaluate the total annual effective dose rates and (ii) assess the relative risk of cancer induction from indoor α-radiation for inhabitants. The average 222 Rn concentrations in all house types were lower than 100 Bq m -3 , but 220 Rn abundances were far higher than 222 Rn, even up to >1000 Bq m -3 in air close to a wall of unfired-soil bricks. The estimated total annual effective dose rates from indoor 222 Rn and 220 Rn and their progenies to residents with daily exposure of 13 h in the various types of houses range from 3.1 to 4.3 mSv a -1 for houses constructed with modified materials, but up to higher than 6 mSv a -1 in houses with raw building materials. The average risk of developing lung cancer as a consequence of a lifetime exposure to indoor α-radiation in affected homes ranges from 3.9% to 14.6%. 220 Rn and its metallic progenies contribute more than 80% of the total average lung cancer risk from total radon, being responsible for a range of 2.7–14.6% of the risk of developing lung cancer.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Decontamination of urban surfaces contaminated with radioactive materials and consequent onsite recycling of the waste water

Enhancing rapid remediation strategies is paramount for recovery after a large-scale nuclear contamination event in an urban environment. Some current strategies recommend use of readily available equipment, materials, and facilities to expedite recovery. For example, applying pressurized water to contaminated surfaces may effectively remove radioactive contamination. In this study, a commercial power washer removes soluble forms of 152 Eu 3 + , 85 Sr 2 + , and 137 Cs + contamination from common porous building materials, and computer simulations characterize the recycling of the resultant contaminated wash water. Pressure washing the porous building materials under spray conditions typical with do-it-yourself units improved decontamination factors (DFs) for 152 Eu compared to low-pressure application of tap water (majority of two-tailed t-test p-values < 0.1), but pressure did not improve DFs for 137 Cs or 85 Sr. For both pressurized and low-pressure applications, adding potassium ions (K + ) to promote ion exchange reactions produced significantly higher DFs for tested radionuclides on asphalt, brick, and concrete. The resultant contaminated wash water can be processed through self-prepared chemical filtration beds of clay and sand. Modeled in a prior study, the beds yielded linear trends (R 2 > 0.98) in sensitivity analyses between most bed configuration variables and bed performance variables, permitting flexible ad-hoc bed design. The experimental and simulation results led to estimates of the remediation rate and waste generated after cleaning 250 m 2 of cesium-contaminated concrete from the combined deployment of a power washer and two different mobile treatment beds. Furthermore, the first treatment bed was designed to reduce treatment time and processed 1900 L of wash solution in 70 min using 880 kg of clay/sand infill material. Designed to reduce the solid waste generated, the second bed processed the same solution volume in 1040 min (17 h) using 170 kg of clay/sand infill material. The results of this analysis warrant further investigation of power washing with recycled salt solution as an effective rapid decontamination method with manageable waste.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2025

Statistical evaluation of microscale stress conditions leading to void nucleation in the weak shock regime

Here, we investigate the heterogeneity of the stress state driven by anisotropic deformation response at the single crystal level through five statistical volume element (SVE) calculations of polycrystalline BCC tantalum. This work focuses on grain boundaries as a prominent material defect type prone to void nucleation based upon experimental observations of predominantly intergranular void nucleation in this material. The SVEs are constructed to be statistically representative of larger volumes of material and are meshed such that mean and standard deviation of grain size and orientation information is reconstructed. The computational meshes feature hexahedral (brick) elements and smooth conformal grain boundaries where significant stress concentration is known to occur, a tail effect of interest in the extreme events process of dynamic ductile damage. An existing micromechanical crystallographic plasticity model shown to capture the single crystal behavior of BCC tantalum well is used to perform the polycrystal calculations. The model includes representation of the non-Schmid effect of non-planar screw dislocation kinetics in tantalum. A three-dimensional stress state time profile predicted by damage modeling of a flyer plate impact experiment is applied as boundary conditions to each SVE. Resulting grain boundary stress state statistics are strongly non-Gaussian. Significant structural evolution is observed within the compressive hold before unloading into tension in the stress profile. Strong angular dependence of grain boundary traction magnitude with shock direction is observed. Non-Schmid effects continue to suggest their influence on propensity of microstructural defect types to nucleate voids. A general void nucleation criterion is proposed using probability theory. The general framework is specified to polycrystalline BCC tantalum in the weak shock regime to include the SVE calculations and literature molecular dynamics calculations of grain boundary void nucleation strength. Probability density functions (PDFs) are used to describe the interaction between the local stress state heterogeneity and the distributed grain boundary void nucleation strength state. A causation entropy maximization procedure removes the requirement for ad hoc selection of a PDF functional form and provides a rigorous procedure for data-based PDF determination. The resulting physically informed PDF describes the spatial appearance frequency of nucleated voids as a function of applied macroscale pressure. Lower length scale physics are thus packaged in a precise and computationally efficient way to provide computational plasticity insight to macroscale dynamic ductile damage models.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Evaluation of SNOLAB background mitigation procedures through the use of an ICP-MS based dust monitoring methodology

Dust particulate fallout on materials in use for rare-event searches is a concerning source of radioactive backgrounds due to the presence of the naturally occurring radionuclides 40 K, 232 Th, 238 U, and their progeny in dust. Much effort is dedicated to inform radioactive backgrounds from dust and evaluate the efficacy of mitigation procedures. A great portion of such effort relies on fallout models and assumed dust composition. Here, in this work, an ICP-MS based methodology was employed for a direct determination of fallout rates of radionuclides and stable isotopes of interest from dust particulate at the SNOLAB facility. Hosted in an active mine, the SNOLAB underground laboratory strives to maintain experimental areas at class 2000 cleanroom level. This work validates the mitigation procedures in place at SNOLAB and informs dust backgrounds during laboratory activities. Fallout rates of major constituents of the local rock were measured two to three orders of magnitude lower in the clean experimental areas compared to non-clean transition areas from the mine to the laboratory. An increase of approximately two orders of magnitude in the fallout rate of stable Pb isotopes was determined in an experimental area during activities involving handling of Pb bricks. Increased 40 K, 232 Th, and 238 U fallout rates were measured in clean experimental areas during activities generating particulate.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2021

An overview of data tools for representing and managing building information and performance data

Building information modeling (BIM) has been widely adopted for representing and exchanging building data across disciplines during building design and construction. However, BIM's use in the building operation phase is limited. With the increasing deployment of low-cost sensors and meters, as well as affordable digital storage and computing technologies, growing volumes of data have been collected from buildings, their energy services systems, and occupants. Such data are crucial to help decision makers understand what, how, and when energy is consumed in buildings—a critical step to improving building performance for energy efficiency, demand flexibility, and resilience. However, practical analyses and use of the collected data are very limited due to various reasons, including poor data quality, ad-hoc representation of data, and lack of data science skills. To unlock value from building data, there is a strong need for a toolchain to curate and represent building information and performance data in common standardized terminologies and schemas, to enable interoperability between tools and applications. This study selected and reviewed 24 data tools based on common use cases of data across the building life cycle, from design to construction, commissioning, operation, and retrofits. The selected data tools are grouped into three categories: (1) data dictionary or terminology, (2) data ontology and schemas, and (3) data platforms. The data are grouped into ten typologies covering most types of data collected in buildings. This study resulted in five main findings: (1) most data representation tools can represent their intended data typologies well, such as Green Button for smart meter data and Brick schema for metadata of sensors in buildings and HVAC systems, but none of the tools cover all ten types of data; (2) there is a need for data schemas to represent the basis of design data and metadata of occupant data; (3) standard terminologies such as those defined in BEDES are only adopted in a few data tools; (4) integrating data across various stages in the building life cycle remains a challenge; and (5) most data tools were developed and maintained by different parties for different purposes, their flexibility and interoperability can be improved to support broader use cases. Finally, recommendations for future research on building data tools are provided for the data and buildings community based on the FAIR principles to make data Findable, Accessible, Interoperable, and Reusable.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2021

Technical and economic feasibility of molten chloride salt thermal energy storage systems

A techno-economic study is performed to assess the feasibility of molten chloride salt thermal energy storage (TES) systems for next generation concentrating solar power. Refractory liners internally insulate tanks to allow tank shells to be constructed from carbon steel. The liner must not be wetted by salt to maintain predictable thermal properties and manageable heat loss out of the tank. The commercial scale tank liner is an anchored brick and mortar design with expansion joints to accommodate thermal expansion. Furthermore, finite element analysis is performed to optimize the thermal and mechanical profile of the tank. Equalizing the shell temperature between the water-cooled foundation and the shell wall is necessary to minimize differential thermomechanical stress and lower overall stress values below industrial allowable limits. The cost of the TES system is estimated to be $60/kWhth, which is four times greater than Department of Energy targets. Solutions to reduce system cost and overall risk are proposed.

14 SOLAR ENERGY↗

DOE OSTI2026

Dirac Fermions and Flat Bands in Phosphorus Carbide Nanotubes: Structural and Quantum Phase Transitions in a Quasi-One-Dimensional Material

Chemically realistic quasi-one-dimensional (1D) materials in which Dirac Fermions and highly degenerate flat bands coexist intrinsically at the Fermi level are exceedingly rare, while representing a highly desirable platform for correlated and topological quantum phenomena. Here, in this work, using specialized symmetry-adapted first-principles calculations we predict a new class of nanomaterials─phosphorus carbide nanotubes (P 2 C 3 NTs)─obtained by rolling monolayer P 2 C 3 , a two-dimensional material shown in a previous letter to host “double Kagome bands”. Both armchair and zigzag P 2 C 3 NTs are stable at room temperature and feature the rare coexistence of Dirac crossings and multiple flat bands at the Fermi level inherited from the underlying honeycomb–Kagome lattice, with the flat bands resilient to elastic deformations. Under large strain, the structure transforms from honeycomb–Kagome to “brick-wall”, accompanied by multiple coupled structural and quantum phase transitions. We also uncover localized edge states, spin splitting from vacancies and dopants, and strain-tunable magnetism. Together, these results establish P 2 C 3 NTs as a chemically specific and mechanically tunable 1D material platform with potential applications in quantum hardware and spintronics.

carbon nanotubes↗

DOE OSTI2025

Bayesian calibration of irradiated graphite property models under high temperatures

Graphite under high temperatures and irradiation is central to advanced reactors. We develop a Bayesian calibration framework for graphite property models that explicitly represents model-data mismatch via a Gaussian-process discrepancy. The approach propagates uncertainty from parameters, experimental noise, and model form, with a hierarchical variance structure to capture group and cross-group noise. Using two predictive models across five grades (IG-110, NBG-18, PCEA, NBG-17, 2114) and four properties-irradiation-induced dimension change, creep, Young’s modulus change ratio, and coefficient of thermal expansion change ratio-we obtain average predictive-error reductions of 54%, 65%, 17%, and 17% when discrepancy is included. We illustrate engineering impact with a multiphysics model of a very-high-temperature reactor prismatic reflector brick, analyzing stresses under high fluence and temperature. Accounting for model discrepancy markedly improves predictive accuracy and provides a robust basis for reliable graphite component design in advanced reactors.

36 - MATERIALS SCIENCE↗