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At least 19 records

Generating synthetic occupants for use in building performance simulation

Occupant behaviour simulation frameworks can employ synthetic populations to characterize occupancy and behavioural patterns in buildings based on observed demographic data at a certain geographical location. For buildings, very few synthetic occupant populations have been generated. This paper uses a Bayesian Networks (BN) structural learning approach to synthesize populations of occupants in a multi-family housing case study. Two additional cases of office occupants and senior housing residents are considered as a cross-case comparison. Furthermore, we draw upon the extended version of drivers-needs-actions-systems (DNAS) framework to guide the selection of variables and data imputation. Our results show that the BN approach is powerful in learning the structure of data sets. The synthetic data sets successfully match the joint distributions of the underlying combined data sets. Experiments on the multi-family housing particularly show better performance than the office and senior housing cases.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Vacancy-tuned magnetism in LaMn x Sb 2

The layered AMP 2 (A = alkali-earth or rare-earth atom, M = transition metal, P = Sb, Bi) compounds are widely studied for their rich magnetism and electronic structure topology. We provide a detailed characterization of the magnetic and transport properties of LaMn x Sb 2 , an understudied member of the AMP 2 family. LaMn x Sb 2 forms with intrinsic Mn vacancies, and we demonstrate that by varying the starting ratio of La, Mn, and Sb, we can synthetically control the Mn occupancy and produce single crystals with x = 0.74 – 0.97. Magnetization and transport measurements indicate LaMn x Sb 2 has a rich temperature-composition (T–x) magnetic phase diagram with physical properties strongly influenced by the Mn occupancy. LaMn x Sb 2 orders antiferromagnetically at T 1 = 130–180 K, where T 1 increases with x. Below T 1 , the T–x phase diagram is complicated. At high x, there is a second transition T 2 that decreases in temperature as x is lowered, vanishing below x ≤ 0.85. A third, first-order, transition T 3 is detected at x ≈ 0.92, and the transition temperature increases as x is lowered, crossing above T 2 near x ≈ 0.9. On moving below x < 0.79, here we find the crystal structure changes from the P 4/nmm arrangement to an I$\bar{4}$2m structure with partially ordered Mn vacancies. The change in crystal structure results in the sudden appearance of two new low-temperature phases and a crossover between regimes of negative and positive magnetoresistance when x ≤ 0.78. Finally, we provide powder neutron diffraction for x = 0.93, and find that the high-x compositions first adopt a G-type antiferromagnetic structure with the Mn moments aligned within the ab plane, which is followed upon further cooling by a second transition to a different, noncollinear structure where the moments are rotated within the basal plane. Our results demonstrate that LaMn x Sb 2 is a highly tunable material with six unique magnetically ordered phases, depending on T and x.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Novel Functional Thermal Energy Storage Materials for Buildings Applications

The leakage of solid-liquid phase change materials (PCMs) tremendously limits their long-term application in thermal energy storage (TES). In this work, we present durable and form-stable shape-stabilized PCMs (ss-PCMs) for TES in building envelopes. These ss-PCMs are fabricated by encapsulating polyethylene glycol (PEG) consisting of different molecular weights within mesoporous magnesium oxide and silica dioxide. For the first time, the phase transition temperature (Tt) of ss-PCMs has been fine-tuned synthetically to be comfortable to building occupants by utilizing PEG blends with molecular weights of 600 and 800 g/mol. Several parameters, including surface hydrophilicity/hydrophobicity, surface area, and PCM loading percentage, have been studied to maximize the latent heat enthalpy for high energy efficiency and maintain form stability. The best ss-PCM candidate with suitable Tt and appreciable latent heat enthalpy exhibits a repeatable phase change behavior for up to 1,000 thermal cycles without leakage, which provides a promising solution for durable TES in buildings. The Tt tunability extends its application over a wider temperature range beyond buildings.

building envelope↗

Sharing is caring: An extensive analysis of parameter-based transfer learning for the prediction of building thermal dynamics

In recent years deep neural networks have been proposed as a lightweight data-driven model to capture high-dimensional, nonlinear physical processes to predict building thermal responses. However, the need of a large amount of data for the training process of deep neural networks clashes with the potential limited data availability in most existing or new buildings. Transfer learning aims to enhance the performance of a target learner exploiting knowledge from related and similar environments. This study conducted a suite of experiments that leveraged 250 data-driven models based on a synthetic dataset of a building archetype to study the influence of data availability, energy efficiency level, occupancy and climate for the transfer process of thermal dynamics. The performance of the transfer learning process was compared against a classical machine learning approach. Here, the results suggest that building thermal dynamics can be effectively transferred under the same climatic conditions, increasing performance when dealing with different occupancy schedules, efficiency levels and low data availability. Furthermore, the paper compares the performance of both transfer learning and machine learning approaches in an online fashion, to support the implementation in real-world deployment.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Simulation of Stark-broadened Hydrogen Balmer-line Shapes for DA White Dwarf Synthetic Spectra

Abstract White dwarfs (WDs) are useful across a wide range of astrophysical contexts. The appropriate interpretation of their spectra relies on the accuracy of WD atmosphere models. One essential ingredient of atmosphere models is the theory used for the broadening of spectral lines. To date, the models have relied on Vidal et al., known as the unified theory of line broadening (VCS). There have since been advancements in the theory; however, the calculations used in model atmosphere codes have only received minor updates. Meanwhile, advances in instrumentation and data have uncovered indications of inaccuracies: spectroscopic temperatures are roughly 10% higher and spectroscopic masses are roughly 0.1 M ⊙ higher than their photometric counterparts. The evidence suggests that VCS-based treatments of line profiles may be at least partly responsible. Gomez et al. developed a simulation-based line-profile code Xenomorph using an improved theoretical treatment that can be used to inform questions around the discrepancy. However, the code required revisions to sufficiently decrease noise for use in model spectra and to make it computationally tractable and physically realistic. In particular, we investigate three additional physical effects that are not captured in the VCS calculations: ion dynamics, higher-order multipole expansion, and an expanded basis set. We also implement a simulation-based approach to occupation probability. The present study limits the scope to the first three hydrogen Balmer transitions (H α , H β , and H γ ). We find that screening effects and occupation probability have the largest effects on the line shapes and will likely have important consequences in stellar synthetic spectra.

79 ASTRONOMY AND ASTROPHYSICS↗

Quenching Effects on Iron Site Partitioning in the Apollo 17 Orange Glass Composition

Mare petrogenesis and the structure of the lunar interior were studied. Analyses of the spectral signatures of glasses was useful to remote sensing applications in areas of the moon where glass is in significant proportions in the lunar soil. The studies provided information on Fe site occupancies in glasses, which are used to construe oxygen fugacities at the lunar surface. Data were obtained through work on synthetic analogues of lunar glasses. However, recent Mossbauer studies of an Apollo 15 green glass composition have shown that synthetic glasses are extremely sensitive to variations in quenching media. Glass structure and Fe(3+)/Fe(2+) ratios are strongly controlled by quenching conditions, which may mask the effects of the original glass' formation temperature or oxygen partial pressure. Synthetic glasses were often run at low fugacities on Pt wires. The effects of quench media on the Apollo 17 orange glass composition are considered.

Dyar, M. D.↗

Demographic Information Incorporated Household Energy Consumption Analysis

The high energy consumption from residential buildings provides them large potential to participate in demand response programs. To design appropriate demand response programs for residential buildings, it is important for electric utilities to know the energy consumption characteristics for different types of households so that utilities can send requests to the groups with a higher possibility to successfully respond. In this paper, we develop a load model to generate synthetic load profiles for different types of households incorporating demographical information including Current Population Survey data set and American Time Use Survey data set. The details of each data set and the details of the load models are presented. The synthetic household load profiles are generated by the load model and clustered into different groups based on state, age, number of occupants, income level, and city of the household. The average energy consumption characteristics for different groups of households are analyzed and compared, which will help electric utilities issue demand response signals to appropriate households.

building loads↗

Demographic Information Incorporated Household Energy Consumption Analysis: Preprint

The high energy consumption from residential buildings provides them large potential to participate in demand response programs. To design appropriate demand response programs for residential buildings, it is important for electric utilities to know the energy consumption characteristics for different types of households so that utilities can send requests to the groups with a higher possibility to successfully respond. In this paper, we develop a load model to generate synthetic load profiles for different types of households incorporating demographical information including Current Population Survey data set and American Time Use Survey data set. The details of each data set and the details of the load models are presented. The synthetic household load profiles are generated by the load model and clustered into different groups based on state, age, number of occupants, income level, and city of the household. The average energy consumption characteristics for different groups of households are analyzed and compared, which will help electric utilities issue demand response signals to appropriate households.

building loads↗

Demographic Information Incorporated Household Energy Consumption Analysis

The high energy consumption from residential buildings provides them large potential to participate in demand response programs. To design appropriate demand response programs for residential buildings, it is important for electric utilities to know the energy consumption characteristics for different types of households so that utilities can send requests to the groups with a higher possibility to successfully respond. In this paper, we develop a load model to generate synthetic load profiles for different types of households incorporating demographical information including Current Population Survey data set and American Time Use Survey data set. The details of each data set and the details of the load models are presented. The synthetic household load profiles are generated by the load model and clustered into different groups based on state, age, number of occupants, income level, and city of the household. The average energy consumption characteristics for different groups of households are analyzed and compared, which will help electric utilities issue demand response signals to appropriate households.

building loads↗

Reactions of Np(VI) and Pu(VI) with Phenanthroline Result in Bending the [NpVIO2]2+ Unit and a Reduced Pu(V) Species

Despite decades of actinyl chemistry, genuinely bent actinyl structures remain rare beyond uranium. We report the first crystallographic characterization of a bent neptunyl(VI) complex, NpO 2 Cl 2 (phen) 2, along with a linear plutonyl species that, unexpectedly, adopts the +V oxidation state. Coordination of two 1,10-phenanthroline ligands to NpO 2 2+ enforces pronounced bending of the O yl –Np–O yl unit to 162° through steric clashes with the axial phenathroline ligand, representing the sharpest angle reported for any neptunyl(VI) complex. In contrast, synthesis with PuO 2 2+ produces a reduced linear Pu(V) species, PuO 2 Cl(phen) 2, underscoring the redox lability and the reluctance of plutonium to distort. Raman and IR spectra yield the first experimental stretching and interaction force constants for plutonyl(V). Comparison with values for plutonyl(VI) and bent and linear uranyl(VI) and neptunyl(VI) compounds shows that reduction perturbs the actinyl bond more than bending within one oxidation state. Electrochemical and spectroscopic studies clarify phenanthroline binding to Pu(VI) and the system’s reactivity. Quantum chemical calculations indicate that bending is energetically favored in the U–Np–Pu series, but the stabilization energy decreases as the actinide atomic number increases. NBO and QTAIM analyses reveal systematic trends: increasing 5f occupancy and decreasing An–O yl bond covalency from U to Pu. These results demonstrate that ligand-induced bending in neptunyl(VI) species is not only electronically feasible but also synthetically achievable, though plutonyl(VI) is constrained by redox reactivity. This work expands the frontier of nonlinear actinyl chemistry and illuminates how structure, oxidation state, and electronic configuration interrelate across the actinyl series.

actinides↗

Using spacecraft trace contaminant control systems to cure sick building syndrome

Many residential and commercial buildings with centralized, recirculating, heating ventilation and air conditioning systems suffer from 'Sick Building Syndrome.' Ventilation rates are reduced to save energy costs, synthetic building materials off-gas contaminants, and unsafe levels of volatile organic compounds (VOC's) accumulate. These unsafe levels of contaminants can cause irritation of eyes and throat, fatigue and dizziness to building occupants. Increased ventilation, the primary method of treating Sick Building Syndrome is expensive (due to increased energy costs) and recently, the effectiveness of increased ventilation has been questioned. On spacecraft venting is not allowed, so the primary methods of air quality control are; source control, active filtering, and destruction of VOC's. Four non-venting contaminant removal technologies; strict material selection to provide source control, ambient temperature catalytic oxidation, photocatalytic oxidation, and uptake by higher plants, may have potential application for indoor air quality control.

Graf, John C.↗

Qualification Status of Non-Asbestos Internal Insulation in the Reusable Solid Rocket Motor Program

This paper provides a status of the qualification efforts associated with NASA's RSRMV non-asbestos internal insulation program. For many years, NASA has been actively engaged in removal of asbestos from the shuttle RSRM motors due to occupation health concerns where technicians are working with an EPA banned material. Careful laboratory and subscale testing has lead to the downselect of a organic fiber known as Polybenzimidazol to replace the asbestos fiber filler in the existing synthetic rubber copolymer Nitrile Butadiene - now named PBI/NBR. Manufacturing, processing, and layup of the new material has been a challenge due to the differences in the baseline shuttle RSRM internal insulator properties and PBI/NBR material properties. For this study, data gathering and reduction procedures for thermal and chemical property characterization for the new candidate material are discussed. Difficulties with test procedures, implementation of properties into the Charring Material Ablator (CMA) codes, and results correlation with static motor fire data are provided. After two successful five segment motor firings using the PBI/NBR insulator, performance results for the new material look good and the material should eventually be qualified for man rated use in large solid rocket motor applications.

Clayton, Louie↗

Investigation of Synthetic Mg(1.3)V(1.7)O4 Spinel with MgO Inclusions: Case Study of a Spinel with an Apparently occupied Interstitial Site

A magnesium vanadate spinel crystal, ideally MgV2O4, synthesized at 1 bar, 1200 C and equilibrated under FMQ + 1.3 log f(sub o2) condition, was investigated using single-crystal X-ray diffraction, electron microprobe, and electron backscatter (EBSD). The initial X-ray structure refinements gave tetrahedral and octahedral site occupancies, along with the presence of 0.053 apfu Mg at an interstitial octahedral site . Back-scattered electron (BSE) images and electron microprobe analyses revealed the existence of an Mg-rich phase in the spinel matrix, which was too small (less than or equal to 3microns) for an accurate chemical determination. The EBSD analysis combined with X-ray energy dispersive spectroscop[y (XEDS) suggested that the Mg-rich inclusions are periclase oriented coherently with the spinel matrix. The final structure refinements were optimized by subtracting the X-ray intensity contributions (approx. 9%) of periclase reflections, which eliminated the interstitial Mg. This study provides insight into possible origins of refined interstitial cations reported in the the literature for spinel, and points to the difficulty of using only X-ray diffraction data to distinguish a spinel with interstitial cations from one with coherently oriented MgO inclusions.

Uchida, Hinako↗

Predicting Building Envelope Construction from In-Situ Thermal Testing

When embarking on a retrofit of a building envelope, it is critical to understand the composition of its assembly. This practice is currently done by destructive and invasive material testing or demolition, which is sometimes not possible when in historic or protected buildings. To address this problem, in-situ thermal testing can be utilized along with machine learning classification algorithms to infer the composition of an assembly. In this paper, a proof-of-concept K-nearest neighbors classification model is developed to classify assembly composition from effective thermal resistance, effective thermal mass, and assembly cladding. This model was trained and tested utilizing a synthetic dataset producing an F1-score of 94.6%. This model was also validated with experimental data from a 100-year old wall assembly, confirming the model’s real-world validity. The paper presents a framework for inferring as-built envelope assemblies, all without having to damage or disturb the building and its occupants.

Pilet, Tyler J.↗

Online and Offline Data Quality Monitoring for the Mu2e Calorimeter

This thesis presents the design, implementation, and validation of a calorimeter Data Quality Monitoring (DQM) toolchain for the Mu2e experiment at Fermilab. Mu2e searches for charged lepton flavor violation via coherent muon-to-electron conversion in the field of an aluminum nucleus, $\mu^- Al \rightarrow e^-Al$, a process whose observation would constitute clear evidence of physics beyond the Standard Model. Achieving target sensitivity requires stringent control of detector performance and data integrity during acquisition, as subtle issues in readout configuration, data formatting, or electronics behavior can compromise reconstruction and bias downstream analyzes. To address these challenges, this work develops a multi-layer DQM approach spanning both raw data validation and reconstructed digi-level diagnostics. At the low level, a fragment analysis component performs word- and bit-field decoding of calorimeter readout blocks, enabling sanity checks of the expected structure and producing detailed error and integrity statistics useful for commissioning and troubleshooting. At the digi level, the CaloDigiDQM analyzer is implemented within the art framework and transforms each CaloDigiCollection into a structured hierarchy of ROOT histograms designed for fast drill-down diagnostics. The module generates coherent monitoring views at global, disk, board, and channel granularity, including occupancy, waveform-derived features (baseline, RMS, peak amplitude and position), and left-right sensor consistency metrics. Detector-aware channel-to-electronics mapping is performed through the conditions system (CaloDAQMap), ensuring that diagnostics remain aligned with hardware identifiers used in operations. For end-to-end testing without reliance on live DAQ data, a synthetic CaloDigi producer is developed to generate realistic waveforms with controlled noise and pulse shapes. The resulting system supports both offline ROOT-file production and online operation, including optional histogram streaming through otsdaq via ots::HistoSender. This toolchain provides a practical and scalable foundation for calorimeter commissioning and stable data collection, enabling early detection of anomalies and reducing operational risk for Mu2e.

Vakulenko, Mark [Drew U.] (ORCID:0009000276197818)↗

Enhanced pozzolanic reactivity in hydrogen-form zeolites as supplementary cementitious materials

Pozzolans rich in silica and alumina react with lime to form cementing compounds and are incorporated into portland cement as supplementary cementitious materials (SCMs). However, pozzolanic reactions progress slower than portland cement hydration, limiting their use in modern construction due to insufficient early-age strength. Hence, alternative SCMs that enable faster pozzolanic reactions are necessary including synthetic zeolites, which have high surface areas and compositional purity that indicate the possibility of rapid pozzolanic reactivity. Synthetic zeolites with varying cation composition (Na-zeolite, H-zeolite), SiO 2 /Al 2 O 3 ratio, and framework type were evaluated for pozzolanic reactivity via Ca(OH) 2 consumption using ion exchange and in-situ X-ray diffraction experiments. Na-zeolites exhibited limited exchange reactions with KOH and Ca(OH) 2 due to the occupancy of acid sites by Na + and hydroxyl groups. Meanwhile, H-zeolites readily adsorbed K + and Ca 2+ from a hydroxide solution by exchanging cations with H + at Brønsted acid sites or cation adsorption at vacant acid sites. By adsorbing cations, the H-zeolite reduced the pH and increased Ca 2+ solubility to promote pozzolanic reactions in a system where Ca(OH) 2 dissolution/diffusion was a rate limiting factor. High H-zeolite reactivity resulted in 0.8 g of Ca(OH) 2 consumed per 1 g of zeolites after 16 h of reaction versus 0.4 g of Ca(OH) 2 consumed per 1 g of Na-zeolite. The H-zeolite modulated the pore fluid alkalinity and created a low-density amorphous silicate phase via mechanisms analogous to two-step C-S-H nucleation experiments. Finally, controlling these reaction mechanisms is key to developing next generation pozzolanic cementitious systems with comparable hydration rates to portland cement.

36 MATERIALS SCIENCE↗

Agent-based simulations of shared automated vehicle operations: reflecting travel-party size, season and day-of-week demand variations

Here, this paper explores the effects of day of week and season of year demand variations for shared rides, along with realistic travel party sizes, on shared autonomous vehicle (SAV) services across the Austin, Texas region. Using the agent-based POLARIS program, synthetic person-trips that reflect travel-party size (from one to four persons) and demand variations over days and months, as evident in the National Household Travel Survey data were simulated in each scenario over a 24 h travel day. Results show that realistic party sizes can bring considerable changes to SAV fleet performance, including up to 8.5% higher service rates (number of requests accepted within 15 min), 5 min shorter journey times (wait time + travel time), 28% higher vehicle occupancies on weekends, and roughly 4% lower empty fleet VMT. Weekend travel is most impacted by season of year, with weekday travel patterns looking more uniform (thanks to work and school trips). Various performance metrics for the Austin network, like total and empty VMT, change by up to 30% when considering realistic variations in party size and time of year. This paper underscores the value of recognizing day-to-day and month-to-month variations in travel demand, and the importance of agent-based model equations to reflect travel-party size. Such realism can help quantify SAV seat occupancies more accurately, highlighting the importance of shared mobility. However, it also creates demand and supply issues for operators that now need more information on party size to manage dynamic ride-sharing, or those that may wish to shift their fleet vehicles to other regions for special events to protect profits while offering reasonable wait times to customers throughout the year.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗