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At least 1,225 records · Page 68

Incorporate day-ahead robustness and real-time incentives for electricity market design

In this paper, we propose a two-stage electricity market framework to explore the participation of distributed energy resources (DERs) in a day-ahead (DA) market and a real-time (RT) market. The objective is to determine the optimal bidding strategies of the aggregated DERs in the DA market and generate online incentive signals for DER-owners to optimize the social-welfare taking into account network operational constraints. Distributionally robust optimization is used to explicitly incorporate data-based statistical information of renewable forecasts into the supply/demand decisions in the DA market. We evaluate the conservativeness of bidding strategies distinguished by different risk aversion settings. In the RT market, a bi-level time-varying optimization problem is proposed to design the online incentive signals to tradeoff the RT imbalance penalty for distribution system operators (DSOs) and the costs of individual DER-owners. This enables tracking their optimal dispatch to provide fast balancing services, in the presence of time-varying network states while satisfying the voltage regulation requirement. Simulation results on both DA wholesale market and RT balancing market demonstrate the necessity of this two-stage design, and its robustness to uncertainties, the performance of convergence, the tracking ability and the feasibility of the resulting network operations.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Adaptive primal–dual control for distributed energy resource management

With the increased adoption of distributed energy resources (DERs) in distribution networks, their coordinated control with a DER management system (DERMS) that provides grid services (e.g., voltage regulation, virtual power plant) is becoming more necessary. One particular type of DERMS using primal–dual control has recently been found to be very effective at providing multiple grid services among an aggregation of DERs; however, the main parameter, the primal–dual step size, must be manually tuned for the DERMS to be effective, which can take a considerable amount of engineering time and labor. To this end, we design a simple method that self-tunes the step size(s) and adapts it to changing system conditions. Additionally, it gives the DER management operator the ability to prioritize among possibly competing grid services. Here we evaluate the automatic tuning method on a simulation model of a real-world feeder in Colorado with data obtained from an electric utility. Through a variety of scenarios, we demonstrate that the DERMS with automatically and adaptively tuned step sizes provides higher-quality grid services than a DERMS with a manually tuned step size.

24 POWER TRANSMISSION AND DISTRIBUTION↗

An empirical analysis of supply offers in the ERCOT operating reserves markets

Here, this paper seeks to improve theoretical and empirical understanding of supplier dynamics in wholesale markets for operating reserves, which have been understudied compared to energy markets. We begin by identifying several economic factors that unit owners may consider when submitting offers into operating reserves auctions in two-stage, co-optimized markets common across much of North America. Next, we analyze historical offer data from the Electric Reliability Council of Texas (ERCOT) market to assess whether actual reserve market behavior aligns with expectations based on economic theory, as well as with commonly used assumptions in electricity market modeling efforts. We find that the aggregate supply of operating reserves in ERCOT varies meaningfully over time, becoming more expensive during summer afternoons, which is consistent with theoretical expectations but contradicts the typical modeling assumption of temporally invariant reserve offers. Analysis of offers made by individual units uncovers additional insights, such as the existence of large offer pattern differences by unit owner and the tendency of battery storage units to submit very low offer prices. We conclude by discussing how our findings can be integrated into electricity market modeling assumptions to improve alignment with observed operating reserve offer inputs and pricing outcomes.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Demand response event simulator and risk-aware bidding tool for industrial customers

Incentive Based Demand Response (IBDR) program participation delivers financial benefits to the consumers and resiliency benefits to the electricity grid. Effectively participating in these programs as an industrial consumer requires bidding strategies that balance financial risk with operational constraints. Existing bidding tools tend not to fully incorporate stochastic IBDR event modeling, program specific baseline and payment/penalty calculations, or demand reduction process control schemes that account for the cascading impacts of shutdown in complex facilities. Here, this work presents an IBDR event simulator and risk-aware bidding framework tool integrating three key components: a flexible, parameterized demand response event generator that rigorously accounts for program structures and stochasticity, a demand response operational simulation model that generates explicit control strategies for load reduction, and a Monte Carlo simulator to evaluate financial risk for varied capacity bids. A case study at a wastewater treatment plant participating in PG&E's Capacity Bidding Program demonstrates the framework's utility. In the peak capacity price month of August, optimal bidding by the wastewater treatment plant nets a mean IBDR benefit of $101,000 (67% of the August electricity bill) with 0.4% probability of a financial loss. This framework enables industrial operators to make informed bidding decisions, negotiate better program terms with demand response load aggregators, and analyze energy flexibility investments at their facilities. Ultimately, this work reduces participation barriers in IBDR programs and supports the broader goal of enhancing grid reliability and renewable energy integration.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Stability of plutonium oxide nanoparticles in the presence of montmorillonite and implications for colloid facilitated transport

The physical and chemical stability of PuO 2 nanoparticles (intrinsic colloids) in groundwater will control their transport and may affect the performance of high-level radioactive waste repositories. In this study, we examined the chemical stability of two types of PuO 2 nanoparticles at both 25 and 80 °C. The “alkaline” PuO 2 nanoparticles were prepared by neutralizing an acidic Pu(IV) solution with dilute NaOH to pH ~9.5. The “acidic” PuO 2 nanoparticles were precipitated from 0.1 M nitric acid by heating a Pu(IV) solution at 60–80 °C for 30 min. The chemical stability of these PuO 2 nanoparticles was tested in the presence of montmorillonite, a common mineral in the environment and potentially relevant backfill material in some nuclear waste repository designs. The “alkaline” PuO 2 nanoparticles were found to be unstable over a timescale of months at both 25 and 80 °C, with elevated temperature enhancing their dissolution rates and sorption to montmorillonite. PuO 2 nanoparticle dissolution rates decreased with increasing Pu concentration, consistent with solution saturation. The “acidic” PuO 2 nanoparticles appeared to remain stable for much longer than the “alkaline” PuO2 nanoparticles. The “alkaline” PuO 2 nanoparticle dissolution rate constants were as high as 10 -11.9±0.4 mol m -2 s -1 and 10 -11.2±0.2 mol m -2 s -1 at 25 and 80 °C, respectively, while the “acidic” PuO 2 nanoparticle dissolution rate at 80 °C was 10 -13.5 mol m -2 s -1 . Based on transmission electron microscopy, the “alkaline” and “acidic” PuO 2 nanoparticles were of similar size (2.5–4.5 and 2–3 nm nanoparticles, respectively). However, the “acidic” PuO 2 nanoparticles formed more ordered nanoparticle aggregates. Our results suggest that the specific conditions experienced during PuO 2 nanoparticle formation could significantly affect the stability of PuO 2 in the presence of competing sorption processes and, in turn, the relative importance of intrinsic versus pseudocolloid transport in the environment.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Metal (Fe, Cu, and As) transformation and association within secondary minerals in neutralized acid mine drainage characterized using X-ray absorption spectroscopy

The formation and transformation of secondary minerals in areas affected by neutralized acid mine drainage (AMD) determine the behavior of toxic elements. To better understand the binding form of toxic elements in the secondary minerals, we focused on the distribution of secondary precipitates and heavy metals in neutralized AMD near a typical Cu-polymetallic deposit located in central Tibet. Compared to background values, the average heavy metal (As, Cu, Co, Cu, Mo, Pb, and Zn) content is higher in sediments close to the neutralized AMD drain. X-ray absorption spectroscopy (XAS) characterization shows the Fe in the suspended particulate matter (SPM) first aggregate as small Fe(III) octahedra clusters and then precipitate as ferrihydrite along the river. The XAS results also show the by-products of neutralization-ferrihydrite and sulfate-are the primary forms of Fe and S in the sediments, respectively. Gypsum retains Cu in the sediments via structural fixation, surface adsorption, and surface coprecipitation. The difference of Cu-O coordination number between the SPM and the sediments reveals the Cu sulfate coprecipitation on the surface of gypsum accompanied by SPM transporting along the river. XAS results confirm that ferrihydrite act as an essential sink for heavy metals, especially As. As (III) mineral in the sediment near the neutralized AMD outfall is dissolved and oxidized to arsenate downstream, which then adsorb to ferrihydrite and/or form As(V)-Fe minerals along the river. Gypsum and ferrihydrite have the potential to release heavy metals with changes in water chemistry, which may pose a threat to the safety of drinking water for downstream residents. These results deepen the understanding of the influence of secondary minerals (especially gypsum and ferrihydrite) on the migration and transformation process of heavy metal pollutants in mine drainage system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

UrbanPop: A spatial microsimulation framework for exploring demographic influences on human dynamics

Ensuring the social equity of planning measures in social systems requires an understanding of human dynamics, particularly how individual relationships, activities, and interactions intersect with individual needs. Spatial microsimulation models (SMSMs) support planning for human security goals by representing human dynamics through realistic, georeferenced synthetic populations, that a) provide a complete representation of social systems while b) also protecting individual privacy. In this paper, we present UrbanPop, an open and reproducible SMSM framework for analysis of human dynamics with high spatial, temporal, and demographic resolution. UrbanPop creates synthetic populations of demographically detailed worker and student agents, positioning them first at probable nighttime locations (home), then moving them to probable daytime locations (work/school). Summary aggregations of these populations match the granular detail available at the census block group level in the American Community Survey Summary File (SF), providing realistic approximations of the actual population. UrbanPop users can select particular demographic traits important in their application, resulting in a highly tailored agent population. We first lay out UrbanPop's baseline methodology, including population synthesis, activity modeling, and diagnostics, then demonstrate these capabilities by developing case studies of shifting population distributions and high-risk populations in Knox County, TN during the global COVID-19 pandemic.

60 APPLIED LIFE SCIENCES↗

The microstructure of a selective laser melting (SLM)-fabricated NiTi shape memory alloy with superior tensile property and shape memory recoverability

A selective laser melting (SLM)-fabricated NiTi with superior tensile property and shape memory recoverability was obtained by using a unique stripe rotation scanning strategy. Here, the alloy characteristics, formation mechanisms and evolution in terms of twins, dislocations and precipitations of the alloy were systematically studied. Compared to the conventional smelting-followed-by-machining, the SLM fabrication process involves rapid solidification and repeated heating, which confer distinctive characteristics to the microstructures of SLM-fabricated NiTi alloys. Rapid solidification promotes the formation of a supersaturation solid solution matrix containing a high concentration vacancies, which in turn aggregate to generate a high density of dislocations. During subsequent repeated heating stages, these dislocations occur thermal motion along three directions of <001 > , <111> and <110 >, leading to the formation of thermal kinks, helical dislocations and wave morphology. Simultaneously, precipitated particles Ti 3 Ni 4 repeatedly nucleate and heterogeneous grow with the movement of dislocation. Such precipitation behavior, termed repeated precipitation, has not been previously reported in the conventional NiTi alloys, suggesting that it could be a unique characteristic of such alloy. After martensitic transformation, only two twins, {1 1¯ 1} type I twin and compound twin, are detected. The twinning lamellae of these two twins, where precipitation and dislocation pile-ups exist, often have uneven thickness and chaotic arrangement. Besides, the unique self-accommodated microstructures, such as secondary {1 1¯ 1} type I twin and compound twin with “herring-bone’’ lamellae, which often appear in the deformed or nanocrystalline NiTi, can also be observed. These unique microstructures may confer the distinctive properties to the SLM-fabricated NiTi.

36 MATERIALS SCIENCE↗

Exploring NaCl-PuCl 3 molten salts with machine learning interatomic potentials and graph theory

Actinide molten salts are the basis of the liquid fuels used in molten salt reactors. Due to the inherent difficulties associated with high temperature and hazardous conditions, experimental investigations of fundamental properties of these materials are usually challenging. In this work, we describe the structure and transport of NaCl-PuCl 3 mixtures using computational techniques. Three compositions were considered (16, 25, and 36 mol% PuCl 3 ) over a temperature range (730 – 1257K) using ab initio molecular dynamics, which provided the necessary data sets for training machine learned interatomic potentials. Further, molecular dynamics simulations based on these potentials were then used to determine structure and transport properties. A substantial change was noted in the structure factor when increasing the PuCl 3 content from 25 to 36 mol%. This change is linked to the aggregation of larger Pu 3+ clusters. In addition, the similarity of the atomic environments of metal cations in molten salt systems to their solid states counterparts was investigated using an unsupervised learning technique. Finally, graph theory was employed to explore the structure and size of actinide networks. Consistent with the structure factor, a dense Pu 3+ intermolecular structure is observed within the 36 mol% PuCl 3 mixture. The structure of cation-cation inter-junctions is also discussed. In all cases, the diffusion of Pu 3+ is significantly lower than that of Na + and Cl - .

36 MATERIALS SCIENCE↗

Design and synthesis of astatinated benzothiazole compounds for their potential use in Targeted Alpha Therapy (TAT) strategies to treat Alzheimer's disease-associated amyloid plaques

Alzheimer's disease (AD) is a terminal neurodegenerative disease characterized by the buildup of amyloid fibrils, amorphous aggregates and tauopathies. Several treatment modalities, which rely on various biological processes to reduce disease burden, have been largely ineffective at treating Alzheimer's disease. Targeted alpha therapy (TAT) has demonstrated positive results in the treatment of cancer. Benzothiazole derivatives have been successfully shown to target these plaques and are used in several imaging applications. One such derivative, Flutemetamol (Vizamyl TM ) is an FDA approved diagnostic tool for PET imaging of AD-associated plaques. We report the radiolabeling of benzothiazole derivatives with 211 At, a 7.2 h alpha emitting radionuclide, using a copper catalyzed reaction with a boronic acid precursor molecule. In conclusion, our final compound [ 211 At]3'-At-PIB-OMe had a radiochemical yield of 55% and was found to be stable for at least 3 h in phosphate buffered saline.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Comparing approaches for introducing polycyclic aromatic hydrocarbons to Ge(001) to seed graphene nanoribbon synthesis by CH 4 chemical vapor deposition

Here, we evaluate two approaches for introducing polycyclic aromatic hydrocarbons (PAHs) to a graphene catalyst substrate as part of a two-step chemical vapor deposition (CVD) process for growing graphene nanoribbons (GNRs). In this process, PAHs first form graphene-like seeds on Ge, and then GNRs are subsequently evolved from these PAH-derived seeds via substrate-mediated anisotropic growth kinetics during the CVD of CH4. The first seeding approach sublimes controlled doses of PAH thin films into the CVD chamber, while the second delivers PAHs directly from the vapor phase at set concentrations. Using these two approaches, we measure the dependence of GNR density on PAH dose and compare the experimental results with predictions from a rate model of PAH diffusion, desorption, and clustering. We find that PAHs that more strongly adsorb to the catalyst surface (generally larger PAHs) desirably remain more individualized prior to GNR evolution whereas smaller, more weakly bound PAHs aggregate into larger clusters with various sizes on Ge that are undesirable for synthesizing more monodisperse GNRs. As a result, this work is important because it offers a framework that enables the rational selection and design of seed molecules, advancing anisotropic GNR CVD synthesis.

CVD↗

Future impacts of ozone driven damages on agricultural systems

Current ozone (O 3 ) concentration levels entail significant damages in crop yields around the world. The reaction of the emitted precursors (mostly methane and nitrogen oxides) with solar radiation contribute to O 3 levels that exceed established thresholds for crop damage. This paper shows current and projected (up to 2080) relative yield losses (RYLs) driven by O 3 exposure for different crops and the associated economic damages applying dynamic crop production and prices that are calculated per region and period. We adjust future crop yields in the Global Change Assessment Model (GCAM) to reflect the RYLs and analyze the effects on agricultural markets. We find that the changes (generally reductions) in O 3 precursor emissions in a reference scenario would reduce the agricultural damages, compared to present, for most of the regions, with a few exceptions including India, where higher future O3 concentrations have large negative impacts on crop yields. The annual economic impact of O3 driven losses from 2010-2080 are, in billion US dollars at 2015 prices ($B), 5.0-6.0, 9.8-18.8, 6.7-10.6 and 10.4-12.5 for corn, soybeans, rice and wheat, respectively, with the large losses for wheat and soybeans driven by their comparatively high responses to O 3 . When O 3 effects are explicitly modelled as exogenous yield shocks in future periods, there is a direct impact in future agricultural markets. Therefore, the aggregated net present value (NPV) of crop production would be reduced around by $90.8B at a global level. However, these changes are not distributed evenly across regions, and the net present market value of the crops would increase by up to $118.2B (India) or decrease by up to $59.2B (China).

54 ENVIRONMENTAL SCIENCES↗

Insights from application of a hierarchical spatio-temporal model to an intensive urban black carbon monitoring dataset

Existing regulatory pollutant monitoring networks rely on a small number of centrally located measurement sites that are purposefully sited away from major emission sources. While informative of general air quality trends regionally, these networks often do not fully capture the local variability of air pollution exposure within a community. Recent technological advancements have reduced the cost of sensors, allowing air quality monitoring campaigns with high spatial resolution. The 100×100 black carbon (BC) monitoring network deployed 100 low-cost BC sensors across the 15 km 2 West Oakland, CA community for 100 days in the summer of 2017, producing a nearly continuous site-specific time series of BC concentrations which we aggregated to one-hour averages. Leveraging this dataset, we employed a hierarchical spatio-temporal model to accurately predict local spatio-temporal concentration patterns throughout West Oakland, at locations without monitors (average cross-validated hourly temporal R 2 =0.60). Using our model, we identified spatially varying temporal pollution patterns associated with small-scale geographic features and proximity to local sources. In a sub-sampling analysis, here we demonstrated that fine scale predictions of nearly comparable accuracy can be obtained with our modeling approach by using ~30% of the 100×100 BC network supplemented by a shorter-term high-density campaign.

54 ENVIRONMENTAL SCIENCES↗

Mass spectrometry and spectroscopic characterization of a tetrameric photosystem I supercomplex from Leptolyngbya ohadii , a desiccation-tolerant cyanobacterium

Cyanobacteria inhabiting desert biological soil crusts face the harsh conditions of the desert. They evolved a suite of strategies toward desiccation-hydration cycles mixed with high light irradiations, etc. In this study we purified and characterized the structure and function of Photosystem I (PSI) from Leptolyngbya ohadii, a desiccation-tolerant desert cyanobacterium. We discovered that PSI forms tetrameric (PSI-Tet) aggregate. We investigated it by using sucrose density gradient centrifugation, clear native PAGE, high performance liquid chromatography, mass spectrometry (MS), time-resolved fluorescence (TRF) and time-resolved transient absorption (TA) spectroscopy. MS analysis identified the presence of two PsaB and two PsaL proteins in PSI-Tet and uniquely revealed that PsaLs are N-terminally acetylated in contrast to non-modified PsaL in the trimeric PSI from Synechocystis sp. PCC 6803. Chlorophyll (Chl) a fluorescence decay profiles of the PSI-Tet performed at 77 K revealed two emission bands at ∼690 nm and 725 nm with the former appearing only at early delay time. The main fluorescence emission peak, associated with emission from the low energy Chls a, decays within a few nanoseconds. TA studies demonstrated that the 725 nm emission band is associated with low energy Chls a with absorption band clearly resolved at ∼710 nm at 77 K. As a result, our work suggests that the heterogenous composition of PsaBs and PsaL in PSI-Tet is related with the adaptation mechanisms needed to cope with stressful conditions under which this bacterium naturally grows.

59 BASIC BIOLOGICAL SCIENCES↗

Halophyte biorefinery for polyhydroxyalkanoates production from Ulva sp. Hydrolysate with Haloferax mediterranei in pneumatically agitated bioreactors and ultrasound harvesting

Here, the present study tested the outdoor cultivation of Haloferax mediterranei for PHA production from green macroalgae Ulva sp. in pneumatically agitated bioreactors and applied ultrasonic separation for enhanced settling of archaeal cells. Scaled-up cultivation (40 L) yielded maximum biomass productivity of 50.1 ± 0.11 mg·L -1 ·h -1 with a PHA productivity of 27 ± 0.01 mg·L -1 ·h -1 and conversion yield of 0.107 g PHA per gram UlvaDW. The maximum mass fraction of PHA achieved in biomass was calculated to be 56% w/w. Ultrasonic harvesting of Hfx. mediterranei cells approached 30% removal at energy inputs around 7.8 kWh·m -3 , and indicated no significant aggregation enhancement by Ca 2+ addition. Molecular weight analysis showed an increase in Polydispersity Index (PDI) when the corresponding air velocities were increased suggesting that the polymer was more homogeneous at lower mixing velocities. The current study demonstrated scalable processes for PHA production using Ulva sp. feedstock providing new technologies for halophilic biorefinery.

09 BIOMASS FUELS↗

Longitudinal Multi-omics Reveal Phase-Dependent Viral Adaptive Strategies and Functional Potential During Formation of Algal-bacterial Granular Sludge

Virus-host interactions within microbial aggregates critically influence microbiome function and stability, yet how physicochemical stresses shape the interactive dynamics remains largely unexplored. Here, we investigated virus–host dynamics during the transition of algal-bacterial granular sludge (ABGS) from activated sludge under continuous hydraulic shear using integrated metagenomics and metatranscriptomics. Hydraulic stress initially reduced host a-diversity, which coincided with a marked increase in viral lysogenicity. During this host diversity bottleneck, viral microdiversity increased, and genes related to virion structure and DNA packaging were under positive selection (pN/pS >1). As host diversity recovered, viral microdiversity declined, while viral anti-defense systems (ADS) significantly increased in abundance. Lagged correlation analysis revealed a significant positive correlation between viral ADS and host defense systems (DS), suggesting an evolutionary arms race. Furthermore, active lysogenic infections were accompanied by enrichment of DS and auxiliary viral genes (AVGs) involved in genetic information processing and amino acid metabolism, potentially enhancing host fitness. Overall, our study unveils a phase-dependent co-evolutionary interplay between viruses and hosts during ABGS formation, providing insights into the development and maintenance of microbial structural and functional resilience in engineered ecosystems.

Qi, Huiyuan↗

Multiscale simulations reveal TDP-43 molecular-level interactions driving condensation

The RNA-binding protein TDP-43 is associated with mRNA processing and transport from the nucleus to the cytoplasm. TDP-43 localizes in the nucleus as well as accumulating in cytoplasmic condensates such as stress granules. Aggregation and formation of amyloid-like fibrils of cytoplasmic TDP-43 are hallmarks of numerous neurodegenerative diseases, most strikingly present in >90% of amyotrophic lateral sclerosis (ALS) patients. If excessive accumulation of cytoplasmic TDP-43 causes, or is caused by, neurodegeneration is presently not known. In this work, we use molecular dynamics simulations at multiple resolutions to explore TDP-43 self- and cross-interaction dynamics. A full-length molecular model of TDP-43, all 414 amino acids, was constructed from select structures of the protein functional domains (N-terminal domain, and two RNA recognition motifs, RRM1 and RRM2) and modeling of disordered connecting loops and the low complexity glycine-rich C-terminus domain. All-atom CHARMM36m simulations of single TDP-43 proteins served as guides to construct a coarse-grained Martini 3 model of TDP-43. The Martini model and a coarser implicit solvent Cα model, optimized for disordered proteins, were subsequently used to probe TDP-43 interactions; self-interactions from single-chain full-length TDP-43 simulations, cross-interactions from simulations with two proteins and simulations with assemblies of dozens to hundreds of proteins. Our findings illustrate the utility of different modeling scales for accessing TDP-43 molecular-level interactions and suggest that TDP-43 has numerous interaction preferences or patterns, exhibiting an overall strong, but dynamic, association and driving the formation of biomolecular condensates.

59 BASIC BIOLOGICAL SCIENCES↗

Weather effects on the lifecycle of U.S. Department of Defense equipment replacement (WELDER)

Extreme weather has a direct and significant impact on buildings and infrastructure, resulting in billions of dollars of damage each year. This problem continues to grow as climate patterns change and buildings are exposed to new and different hazards than what they were designed to withstand. In order to better plan for the long-range sustainment, restoration, modernization, and eventual recapitalization of these buildings, organizations with large building portfolios, such as the U.S. Department of Defense (DoD), must have an awareness of the risks that these extreme weather events present. This research aimed to develop an approach to estimate condition loss and reduction in service life for the components of a building due to extreme weather hazards, to understand the risks that may be present in certain buildings and building systems. To achieve this objective, a damage association matrix was developed that categorizes climate hazards, the damage modes that they produce, and the individual component types impacted. This damage matrix formally links state-of-the-art climate model output, which provides projections of the probability of various climate hazards with a damage effects model that quantifies the consequence on component-level condition and service life. This method is applied to an actual portfolio of buildings in a particular geographic location and with a pre-defined component inventory that comprises the building. This approach can be aggregated to the system-, facility-, and site-level thus helping support billions of dollars in recapitalization decisions related to restoration/modernization of facilities.

54 ENVIRONMENTAL SCIENCES↗