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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 847 records · Page 47
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Small field in-air output factors: The role of miniphantom design and dosimeter type

Purpose: The commissioning of treatment planning systems and beam modeling requires measured input parameters. The measurement of relative output in-air, S{sub c} is particularly difficult for small fields. The purpose of this study was to investigate the influence of miniphantom design and detector selection on measured S{sub c} values for small fields and to validate the measurements against Monte Carlo simulations. Methods: Measurements were performed using brass caps (with sidewalls) or tops (no sidewalls) of varying heights and widths. The performance of two unshielded diodes (60012 and SFD), EBT2 radiochromic film, and a fiber optic dosimeter (FOD) were compared for fields defined by MLCs (5–100 mm) and SRS cones (4–30 mm) on a Varian Novalis linear accelerator. Monte Carlo simulations were performed to theoretically predict S{sub c} as measured by the FOD. Results: For all detectors, S{sub c} agreed to within 1% for fields larger than 10 mm and to within 2.3% for smaller fields. Monte Carlo simulation matched the FOD measurements for all size of cone defined fields to within 0.5%. Conclusions: Miniphantom design is the most important variable for reproducible and accurate measurements of the in-air output ratio, S{sub c}, in small photon fields (less than 30 mm). Sidewalls are not required for fields ≤ 30 mm and tops are therefore preferred over the larger caps. Unlike output measurements in water, S{sub cp,} the selection of detector type for S{sub c} is not critical, provided the active dosimeter volume is small relative to the field size.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2019

Presence and distribution of insect-associated and entomopathogenic fungi in a temperate pine forest soil: An integrated approach

For decades entomopathogenic fungi have garnered interest as possible alternatives to chemical pesticides. However, their ecology outside of agroecosystems demands further study. We assessed the diversity and abundance of entomopathogenic and insect-associated fungi at a loblolly pine forest in North Carolina, USA using culture-dependent and next-generation sequencing libraries. Fungi were isolated using Galleria mellonella larvae, as well as from soil dilutions plated on a selective medium. Isolates were identified using Sanger sequencing of the ITS and LSU rRNA gene regions, and represented 36 OTUs including Metarhizium, Lecanicillium, and Paecilomyces . Additionally, we assessed the chitinolytic potential of isolates and found widespread, variable ability to degrade chitin within and between genera. Phylogenetic analyses resolved several isolates to genus, with some forming clades with other insect-associated taxa, as well as with fungi associated with plant tissues. Saprophytes were widely distributed in soil, while entomopathogens were less abundant and present primarily in the top two cm of the soil. Furthermore, the similarity between culture-dependent and next-generation sequencing results demonstrates that both methods can be used concurrently in this system to study the ecology of entomopathogenic fungi.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Optimized Dispatch of Distributed Energy Resources for Resiliency and Power Quality Improvements at the Grid-Edge

Distributed Energy Resources (DERs) installed on low-voltage distribution systems, both utility-owned and nonutility owned may be employed to make improvements to system resiliency and power quality, in addition to simply serving load demand. By selectively dispatching active and reactive power from these existing DERs, improvements in voltage profiles and service availability during adverse events may be achieved. Further benefits can be gained by optimally choosing which DERs to dispatch power from, and the distribution of power from those DERs. For a given operating condition, using Linear Programming methods, optimal power dispatch values for individual DERs can be determined, while considering variables such as voltage gains, losses in the lines and the DERs, and DER reserve capacities. One such optimization technique is developed in this paper, and results from a real-time simulation study on a modified IEEE 13-bus distribution system with three DERs, are being presented. The operation of the optimized DER selection and dispatch algorithm is shown during normal operation of the transmission system when the DERs operate in grid-connected mode. Similar analyses can drive decision making during transmission system failure when the DERs operate in grid-forming or islanded mode.

Chowdhury, Prithwiraj Roy↗
DOE OSTI2017

Assessing Intra-arterial Complications of Planning and Treatment Angiograms for Y-90 Radioembolization

PurposeTo report hepatic arterial-related complications encountered during planning and treatment angiograms for radioembolization and understand any potential-associated risk factors.Materials and Methods518 mapping or treatment angiograms for 180 patients with primary or metastatic disease to the liver treated by Yttrium-90 radioembolization between 2/2010 and 12/2015 were retrospectively reviewed. Intra-procedural complications were recorded per SIR guidelines. Patient demographics, indication for treatment, prior exposure to chemotherapeutic agents, operator experience, and disease burden were reviewed. Technical variables including type of radioembolic (glass vs. resin microspheres), indication for angiography (mapping vs. treatment), variant anatomy, and attempts at coil embolization were also assessed.ResultsThirteen (13/518, 2.5%) arterial-related complications occurred in 13 patients. All but two complications resulted during transcatheter coil embolization to prevent non-target embolization. Complications included coil migration (n = 6), arterial dissection (n = 2), focal vessel perforation (n = 2), arterial thrombus (n = 2), and vasospasm prohibiting further arterial sub-selection (n = 1). Transarterial coiling was identified as a significant risk factor of complications on both univariate and multivariate regression analysis (odds ratio 7.8, P = 0.004). Usage of resin microspheres was also a significant risk factor (odds ratio 9.5, P = 0.042). No other technical parameters or pre-procedural variables were significant after adjusting for confounding on multivariate analysis (P > 0.05).ConclusionIntra-procedural hepatic arterial complications encountered during radioembolization were infrequent but occurred mainly during coil embolization to prevent non-target delivery to extra-hepatic arteries.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2022

The Application of a Genetic Algorithm to the Optimization of a Mesoscale Model for Emergency Response

Besides solving the equations of momentum, heat, and moisture transport on the model grid, mesoscale weather models must account for subgrid-scale processes that affect the resolved model variables. These are simulated with model parameterizations, which often rely on values preset by the user. Such “free” model parameters, along with others set to initialize the model, are often poorly constrained, requiring that a user select each from a range of plausible values. Finding the values to optimize any forecasting tool can be accomplished with a search algorithm, and one such process—the genetic algorithm (GA)—has become especially popular. As applied to modeling, GAs represent a Darwinian process: an ensemble of simulations is run with a different set of parameter values for each member, and the members subsequently judged to be most accurate are selected as “parents” who pass their parameters onto a new generation. At the U.S. Department of Energy’s Savannah River Site in South Carolina, we are applying a GA to the Regional Atmospheric Modeling System (RAMS) mesoscale weather model, which supplies input to a model to simulate the dispersion of an airborne contaminant as part of the site’s emergency response preparations. An ensemble of forecasts is run each day, weather data are used to “score” the individual members of the ensemble, and the parameters from the best members are used for the next day’s forecasts. As meteorological conditions change, the parameters change as well, maintaining a model configuration that is best adapted to atmospheric conditions. Significance Statement We wanted to develop a forecasting system by which a weather model is run over the Savannah River Site each day and repeatedly adjusted according to how well it performed the previous day. To run the model, a series of values (parameters) must be set to control how the model will calculate winds, temperatures, and other desired variables. Each day the model was run several times using different combinations of these parameters and later compared with observed meteorological conditions. Parameters that produced the most accurate forecasts were preferentially reused to create the forecasts for the next day. The process was tested for the summer of 2020 and exhibited lower errors than forecasts produced by the model using default values of the parameters.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

SU-E-J-262: Variability in Texture Analysis of Gynecological Tumors in the Context of An 18F-FDG PET Adaptive Protocol

Purpose: This study examines the effect on texture analysis due to variable reconstruction of PET images in the context of an adaptive FDG PET protocol for node positive gynecologic cancer patients. By measuring variability in texture features from baseline and intra-treatment PET-CT, we can isolate unreliable texture features due to large variation. Methods: A subset of seven patients with node positive gynecological cancers visible on PET was selected for this study. Prescribed dose varied between 45–50.4Gy, with a 55–70Gy boost to the PET positive nodes. A baseline and intratreatment (between 30–36Gy) PET-CT were obtained on a Siemens Biograph mCT. Each clinical PET image set was reconstructed 6 times using a TrueX+TOF algorithm with varying iterations and Gaussian filter. Baseline and intra-treatment primary GTVs were segmented using PET Edge (MIM Software Inc., Cleveland, OH), a semi-automatic gradient-based algorithm, on the clinical PET and transferred to the other reconstructed sets. Using an in-house MATLAB program, four 3D texture matrices describing relationships between voxel intensities in the GTV were generated: co-occurrence, run length, size zone, and neighborhood difference. From these, 39 textural features characterizing texture were calculated in addition to SUV histogram features. The percent variability among parameters was first calculated. Each reconstructed texture feature from baseline and intra-treatment per patient was normalized to the clinical baseline scan and compared using the Wilcoxon signed-rank test in order to isolate variations due to reconstruction parameters. Results: For the baseline scans, 13 texture features showed a mean range greater than 10%. For the intra scans, 28 texture features showed a mean range greater than 10%. Comparing baseline to intra scans, 25 texture features showed p <0.05. Conclusion: Variability due to different reconstruction parameters increased with treatment, however, the majority of texture features showed significant changes during treatment independent of reconstruction effects.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

On the challenges facing the handling of solid biomass feedstocks: On the Challenges Facing the Handling of Solid Biomass Feedstocks

With a major global emphasis on the management of waste, alternative resources and a shift to environmentally sustainable technologies, demand for large volumes of heterogeneous solid biomass feedstocks for energy or chemical use is expected to rise significantly. In transforming a sporadic supply of a low-value, highly variable product, to continuous and controlled high throughput systems, a thorough understanding of the feedstock properties will increase in importance. Appropriate characterisation tests are necessary to define technical specification and selection criteria for handling equipment and to appraise the requirement and location for additional processes or pre-treatment to be integrated into the handling chain. Such tests may also influence the material characteristics to be used in the conversion process. In this paper, we discuss the main feedstock attributes associated with a number of handling chain phases and the approach to obtain them. Lastly, the framework for a holistic approach to the characterisation and design of biomass feedstock handling systems for further development and practical implementation is also proposed.

09 BIOMASS FUELS↗
DOE OSTI2016

A multi-objective optimization approach to optimal sensor location problem in $\mathrm{IGCC}$ power plants

Integrated Gasification Combined Cycle (IGCC) power plants provide a cleaner and more efficient way to obtain energy from coal. In order to operate an IGCC power plant in a safe and stable manner, several input and output process parameters need to be monitored. However, due to economic and operational constraints, it is infeasible to place sensors at every input and output process parameter location. Hence, it becomes important to select the most effective sensor locations which lead to maximum information gain about the plant conditions. Practical issues present in an IGCC power plant, such as harsh physical conditions and variability in process parameters, make the optimal sensor location problem an especially complicated one. Further, sensors can have multiple objectives and they can produce uncertainties due to measurement errors. Here this work considers hybrid hardware and virtual sensing for advanced power systems with multiple objectives. In order to solve this real world large scale problem, we use a novel algorithm called Better Optimization of Nonlinear Uncertain Systems (BONUS). BONUS works in probability distribution space and avoids sampling for each optimization and derivative calculations iterations. A new algorithm for multi-objective optimization is also developed specifically for problem. The result of this nonlinear stochastic multi-objective problem is the non-dominated, or Pareto set, which provides trade-offs between various objectives like observability, cost, and thermal efficiency. This is the first attempt at solving the problem of optimal sensor deployment in advanced power plants, with consideration of hybrid hardware and virtual sensing and incorporation of uncertainty with multiple objectives.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2015

Defect topologies in chiral liquid crystals confined to mesoscopic channels

We present Monte Carlo simulations in the grand canonical and canonical ensembles of a chiral liquid crystal confined to mesochannels of variable sizes and geometries. The mesochannels are taken to be quasi-infinite in one dimension but finite in the two other directions. Under thermodynamic conditions chosen and for a selected value of the chirality coupling constant, the bulk liquid crystal exhibits structural characteristics of a blue phase II. This is established through the tetrahedral symmetry of disclination lines and the characteristic simple-cubic arrangement of double-twist helices formed by the liquid-crystal molecules along all three axes of a Cartesian coordinate system. If the blue phase II is then exposed to confinement, the interplay between its helical structure, various anchoring conditions at the walls of the mesochannels, and the shape of the mesochannels gives rise to a broad variety of novel, qualitative disclination-line structures that are reported here for the first time.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Dark Energy Survey year 1 results: Galaxy clustering for combined probes

We measure the clustering of DES year 1 galaxies that are intended to be combined with weak lensing samples in order to produce precise cosmological constraints from the joint analysis of large-scale structure and lensing correlations. Two-point correlation functions are measured for a sample of 6.6×10 5 luminous red galaxies selected using the redMaGiC algorithm over an area of 1321 square degrees, in the redshift range 0.15 z /(1+z)=0.017. We quantify and correct spurious correlations induced by spatially variable survey properties, testing their impact on the clustering measurements and covariance. We demonstrate the sample’s robustness by testing for stellar contamination, for potential biases that could arise from the systematic correction, and for the consistency between the two-point auto- and cross-correlation functions. We show that the corrections we apply have a significant impact on the resultant measurement of cosmological parameters, but that the results are robust against arbitrary choices in the correction method. We find the linear galaxy bias in each redshift bin in a fiducial cosmology to be b(σ 8 /0.81)| z=0.24 =1.40±0.07, b(σ 8 /0.81)| z=0.38 =1.60±0.05, b(σ 8 /0.81)| z=0.53 =1.60±0.04 for galaxies with luminosities L/L * >0.5, b(σ 8 /0.81)| z=0.68 =1.93±0.04 for L/L * >1 and b(σ 8 /0.81)| z=0.83 =1.98±0.07 for L/L * >1.5, broadly consistent with expectations for the redshift and luminosity dependence of the bias of red galaxies. We show these measurements to be consistent with the linear bias obtained from tangential shear measurements.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Measurements of Density and Sound Speed in Mixtures Relevant to Supercritical CO2 Cycles

Abstract The objective of this research is to validate properties of mixtures relevant to supercritical carbon dioxide (sCO2) power cycles. Direct-fired sCO2 cycles are a promising technology for the future power generation systems. The working fluid of sCO2 cycles will be near and above critical point of CO2. One of the challenges is that the simulation of mixtures should consider real gas behavior. Expected operating conditions of Allam cycles reach up to 300 bar and 1000 °C. Characterizing the mixtures at the extreme conditions is an important issue in current researches and industrial applications. Thermophysical properties of mixtures may be beyond the valid range of the widely used database such as NIST REFPROP. Experimental data of mixture properties in the literature are limited which is necessary to develop high-fidelity design tools for sCO2 power cycles. We measured the density and sound speed of several multi-component mixtures. A temperature-controlled high-pressure test cell was used for the density measurements. Sound speed was measured by resonant frequency detection using an external speaker and a piezoelectric pressure sensor. Mixtures studied in this work include carbon dioxide, methane, oxygen, and water vapor. Properties of pure CO2 were measured to show the validity of our technique. Compositions were selected to be close to frozen mixtures at the inlet, mid-progress, and exhaust conditions of a model sCO2 combustor in the previous numerical simulation work. Corresponding reaction progress variables (RPV) were RPV = 0, 0.5, and 1. Temperature and pressure conditions of experiments are 310–450 K and 0–150 bar. In our study, density and sound speed from the NIST REFPROP database agree with experimental measurements within the range of our measurement uncertainties.

Energy & Fuels↗
DOE OSTI2015

Predictive Maturity of Multi-Scale Simulation Models for Fuel Performance

The project proposed to provide a Predictive Maturity Framework with its companion metrics that (1) introduce a formalized, quantitative means to communicate information between interested parties, (2) provide scientifically dependable means to claim completion of Validation and Uncertainty Quantification (VU) activities, and (3) guide the decision makers in the allocation of Nuclear Energy’s resources for code development and physical experiments. The project team proposed to develop this framework based on two complimentary criteria: (1) the extent of experimental evidence available for the calibration of simulation models and (2) the sophistication of the physics incorporated in simulation models. The proposed framework is capable of quantifying the interaction between the required number of physical experiments and degree of physics sophistication. The project team has developed this framework and implemented it with a multi-scale model for simulating creep of a core reactor cladding. The multi-scale model is composed of the viscoplastic self-consistent (VPSC) code at the meso-scale, which represents the visco-plastic behavior and changing properties of a highly anisotropic material and a Finite Element (FE) code at the macro-scale to represent the elastic behavior and apply the loading. The framework developed takes advantage of the transparency provided by partitioned analysis, where independent constituent codes are coupled in an iterative manner. This transparency allows model developers to better understand and remedy the source of biases and uncertainties, whether they stem from the constituents or the coupling interface by exploiting separate-effect experiments conducted within the constituent domain and integral-effect experiments conducted within the full-system domain. The project team has implemented this procedure with the multi- scale VPSC-FE model and demonstrated its ability to improve the predictive capability of the model. Within this framework, the project team has focused on optimizing resource allocation for improving numerical models through further code development and experimentation. Related to further code development, we have developed a code prioritization index (CPI) for coupled numerical models. CPI is implemented to effectively improve the predictive capability of the coupled model by increasing the sophistication of constituent codes. In relation to designing new experiments, we investigated the information gained by the addition of each new experiment used for calibration and bias correction of a simulation model. Additionally, the variability of ‘information gain’ through the design domain has been investigated in order to identify the experiment settings where maximum information gain occurs and thus guide the experimenters in the selection of the experiment settings. This idea was extended to evaluate the information gain from each experiment can be improved by intelligently selecting the experiments, leading to the development of the Batch Sequential Design (BSD) technique. Additionally, we evaluated the importance of sufficiently exploring the domain of applicability in experiment-based validation of high-consequence modeling and simulation by developing a new metric to quantify coverage. This metric has also been incorporated into the design of new experiments. Finally, we have proposed a data-aware calibration approach for the calibration of numerical models. This new method considers the complexity of a numerical model (the number of parameters to be calibrated, parameter uncertainty, and form of the model) and seeks to identify the number of experiments necessary to calibrate the model based on the level of sophistication of the physics. The final component in the project team’s work to improve model calibration and validation methods is the incorporation of robustness to non-probabilistic uncertainty in the input parameters. This is an improvement to model validation and uncertainty quantification stemming beyond the originally proposed scope of the project. We have introduced a new metric for incorporating the concept of robustness into experiment-based validation of numerical models. This project has accounted for the graduation of two Ph.D. students (Kendra Van Buren and Josh Hegenderfer) and two M.S. students (Matthew Egeberg and Parker Shields). One of the doctoral students is now working in the nuclear engineering field and the other one is a post-doctoral fellow at the Los Alamos National Laboratory. Additionally, two more Ph.D. students (Garrison Stevens and Tunc Kulaksiz) who are working towards graduation have been supported by this project.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

Residential Cold Climate Heat Pump (CCHP) w/Variable Speed Technology

This report summarizes the results of a three year program awarded to Unico, Inc. to commercialize a residential cold climate heat pump. Several designs were investigated. Compressors were selected using analysis from Oakridge National Laboratories followed by prototype construction and lab testing in a specially built environmental chamber capable of reaching -30°F. The initial design utilized two variable speed compressors in series with very good capacity results and acceptable efficiency at very cold temperatures. The design was then modified to reduce cost and complexity by redesigning the system using three dual-stage compressors: two in parallel followed by one in series. Extensive testing found significant challenge with oil management, reliability, weight and cost which prevented the system from being fully commercialized. Further analysis of other conceptual designs indicated that these challenges could be overcome in the future.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

A Model Tree Generator (MTG) Framework for Simulating Hydrologic Systems: Application to Reservoir Routing

Data-driven algorithms have been widely used as effective tools to mimic hydrologic systems. Unlike black-box models, decision tree algorithms offer transparent representations of systems and reveal useful information about the underlying process. A popular class of decision tree models is model tree (MT), which is designed for predicting continuous variables. Most MT algorithms employ an exhaustive search mechanism and a pre-defined splitting criterion to generate a piecewise linear model. However, this approach is computationally intensive, and the selection of the splitting criterion can significantly affect the performance of the generated model. These drawbacks can limit the application of MTs to large datasets. To overcome these shortcomings, a new flexible Model Tree Generator (MTG) framework is introduced here. MTG is equipped with several modules to provide a flexible, efficient, and effective tool for generating MTs. The application of the algorithm is demonstrated through simulation of controlled discharge from several reservoirs across the Contiguous United States (CONUS).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

A Method for Integrating an UBEM with GIS for Spatiotemporal Visualization and Analysis

Leveraging Geographic Information Systems (GIS) for spatiotemporal visualization and analysis of simulated UBEM datasets and real-world data simultaneously can assist in identifying opportunities, as well as potential barriers, to energy efficient and climate adaptation strategies. However, current GIS-based models that support interactive exploration of adaptation strategies and future scenarios are scarce and do not easily incorporate building energy use data for visual analysis over time. This paper describes a workflow to integrate simulated building energy consumption data associated with variable energy efficiency scenarios within a GIS platform for interactive spatiotemporal visualization to support climate adaptation decision-making. The contribution of the work presented is in the ability to selectively view and analyze simulated building energy performance data layered with other real-world geospatial data through an automated feedback loop between an UBEM and ArcGIS. An interactive interface is designed in ArcGIS to enable users to explore building performance scenarios spatially and over time. Using a downtown neighborhood in Syracuse, New York, USA, as a case study, preliminary results demonstrate how the workflow provides insight into existing energy use issues and potential for implementing strategies such as energy load shifting or building retrofits. A discussion includes opportunities as well as challenges to the workflow in facilitating understanding of urban energy model outputs by multiple stakeholders in evaluating potential energy efficient strategies.

ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION↗
DOE OSTI2016

Determinacion de la Masa Del Quark Top Usando Variables Leptonicas en el Experimento CMS del LHC

A novel technique for measuring the top quark mass using only leptonic observables is discussed. Top quark pair events with one electron and one muon and at least one jet in the final state are selected in proton-proton collision data collected by the CMS experiment at a center-of-mass energy of 8 TeV, corresponding to an integrated luminosity of 19.7 fb$^{-1}$. Several observables are studied and the transverse momentum distribution of the charged lepton pair originating from the decay of the top quark pair is chosen to extract the top quark mass. After the calibration with simulated events a value of mt=171.7 1.1 (stat.)0.5 (exp.)-3.1+2.5 (th.)+0.8 (p(t)) GeV is measured, where the dominant systematic uncertainties stem from signal modeling.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2019

Collaborative Research On Ecophysiological Controls on Amazonian Precipitation Seasonality And Variability

We developed and deployed a robust and accurate instrumentation package for measurement of solar induced chlorophyll fluorescence (SIF) from above a plant canopy. The sensor collects light from identical up and down facing hemispheric collectors. A fiber optic transmits the collected light (selected by a rotatable prism) to spectrometers located at the base of the tower. Spectra of the down welling and upwelling light were collected alternatively and stored for later analysis. SIF was retrieved by a spectral unmixing approach using high resolution spectra in the 730-760 nm band. Most other ground-based sensors base their analysis on O 2 -alpha band (760-780 nm) for SIF retrieval. We found that the former gave identical results when the atmosphere was clear, but the former was more stable in the cloudy conditions that often prevailed in the Amazon. The mechanical design and software developed for the system are available on request. The sensor was mounted near the top of an 80 m tower at K34 near Manaus in the Brazilian Amazon Forest. The sensor system proved weather-tight and functioned flawlessly over the time of deployment. Our experiment was cut short at 6 months by failure of air conditioning infrastructure at the tower. We found that SIF emitted by canopy was remarkably stable when scaled by the downwelling photosynthetically active radiation or the upwelling near infrared light. We detected a 3.4% increase in SIF over the course of the dry season. This finding is consistent with the observation that several trees in the field of view flushed new leaves in the dry season. We saw no evidence of drought stress or photo damage of the forest canopy during our study.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Moisture Durability Assessment of Selected Well-insulated Wall Assemblies

This report presents the results from studying the hygrothermal performance of two well-insulated wall assemblies, both complying with and exceeding international building codes (IECC 2015 2014, IRC 2015). The hygrothermal performance of walls is affected by a large number of influential parameters (e.g., outdoor and indoor climates, workmanship, material properties). This study was based on a probabilistic risk assessment in which a number of these influential parameters were simulated with their natural variability. The purpose of this approach was to generate simulation results based on laboratory chamber measurements that represent a variety of performances and thus better mimic realistic conditions. In total, laboratory measurements and 6,000 simulations were completed for five different US climate zones. A mold growth indicator (MGI) was used to estimate the risk of mold which potentially can cause moisture durability problems in the selected wall assemblies. Analyzing the possible impact on the indoor climate due to mold was not part of this study. The following conclusions can be reached from analyzing the simulation results. In a hot-humid climate, a higher R-value increases the importance of the airtightness because interior wall materials are at lower temperatures. In a cold climate, indoor humidity levels increase with increased airtightness. Air leakage must be considered in a hygrothermal risk assessment, since air efficiently brings moisture into buildings from either the interior or exterior environment. The sensitivity analysis of this study identifies mitigation strategies. Again, it is important to remark that MGI is an indicator of mold, not an indicator of indoor air quality and that mold is the most conservative indicator for moisture durability issues.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗