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At least 433 records · Page 24

Hygrothermal Simulations of Foundations: Part 1 - Soil Material Properties

Hygrothermal performance of soils coupled to buildings is a complicated process. The computational approach for heat transfer via the ground is well defined (EN-ISO-13370:, 2007) together with simplified methods (Staszczuk, Radon, & Holm). Though the soil moisture transfer is generally ignored, it is proven not negligible (Janssen, Carmeliet, & Hens, 2004). Even though reliable material properties of soils are required to perform realistic hygrothermal calculations of soils coupled to buildings, such material properties have not been well defined in hygrothermal calculations tools. Typical building constructions which are greatly influenced by soils are basements, crawl spaces and slab on grade and reliable hygrothermal performance of such construction are highly requested; as it is ranked within the top 10 Building America Enclosure Research Ideas according to Enclosures STC - Residential Energy Efficiency Stakeholder Meeting, February 29, 2012 Austin, TX. There exists an extensive amount of measurements on soil properties in Soil Science though this information must be gathered as well as adapted to be applicable in Building Science and for hygrothermal simulation purposes. Soil properties are important when analyzing and designing both new building constructions and retrofitting measures, where the outer boundary of the buildings enclosure consists of soil materials. Concerning basement energy retrofits, interior solutions of improving the energy demand has to cooperate with the existing soil properties and must therefore be designed thereafter. In concerns of exterior retrofits, the soil material can be replaced, if needed, with a more suitable filling material, though this approach applies only for basement walls. The soil material beneath the basement floor can naturally not be replaced hence the soil properties of this part of the buildings enclosure still must be taken into consideration. This study is divided into several parts. The intention of the first part is to gather, comprehend and adapt soil properties from soil science. The obtained information must be applicable for Building Science related tasks and validated in hygrothermal calculation tools hence the second part of this study will focus on validation of the implemented soil properties. Basic changes in the software code may be requested as well. Different basement constructions will be created with a hygrothermal calculation tool, WUFI, from which simulations will be compared with existing or on-going measurements. The final outcome of the study is to enable an evaluation of several soil types in several climate zones combined with a number of basement assemblies. The study will define which type of soil together with a certain building construction which is considered most and least reliable in concerns of energy consumption and moisture safety. Further, what influences different soils will have on the total energy loss via the ground and if the performance of a different soils can be measured by a comparison of soil properties solely.

Pallin, Simon B↗

Development of Fe 3 O 4 core–TiO 2 shell nanocomposites and nanoconjugates as a foundation for neuroblastoma radiosensitization

Neuroblastoma is the most common extracranial solid malignancy in childhood which, despite the current progress in radiotherapy and chemotherapy protocols, still has a high mortality rate in high risk tumors. Nanomedicine offers exciting and unexploited opportunities to overcome the shortcomings of conventional medicine. The photocatalytic properties of Fe 3 O 4 core-TiO 2 shell nanocomposites and their potential for cell specific targeting suggest that nanoconstructs produced using Fe 3 O 4 core-TiO 2 shell nanocomposites could be used to enhance radiation effects in neuroblastoma. In this study, we evaluated bare, metaiodobenzylguanidine (MIBG) and 3,4-Dihydroxyphenylacetic acid (DOPAC) coated Fe 3 O4@TiO 2 as potential radiosensitizers for neuroblastoma in vitro. The uptake of bare and MIBG coated nanocomposites modestly sensitized neuroblastoma cells to ionizing radiation. Conversely, cells exposed to DOPAC coated nanocomposites exhibited a five-fold enhanced sensitivity to radiation, increased numbers of radiation induced DNA double-strand breaks, and apoptotic cell death. The addition of a peptide mimic of the epidermal growth factor (EGF) to nanoconjugates coated with MIBG altered their intracellular distribution. Cryo X-ray fluorescence microscopy tomography of frozen hydrated cells treated with these nanoconjugates revealed cytoplasmic as well as nuclear distribution of the nanoconstructs. The intracellular distribution pattern of different nanoconjugates used in this study was different for different nanoconjugate surface molecules. Cells exposed to DOPAC covered nanoconjugates showed the smallest nanoconjugate uptake, with the most prominent pattern of large intracellular aggregates. Interestingly, cells treated with this nanoconjugate also showed the most pronounced radiosensitization effect in combination with the external beam x-ray irradiation. Further studies are necessary to evaluate mechanistic basis for this increased radiosensitization effect. Preliminary studies with the nanoparticles carrying an EGF mimicking peptide showed that this approach to targeting could perhaps be combined with a different approach to radiosensitization – use of nanoconjugates in combination with the radioactive iodine. Much additional work will be necessary in order to evaluate possible benefits of targeted nanoconjugates carrying radionuclides.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DPSIR-ESA Vulnerability Assessment (DEVA) Framework: Synthesis, Foundational Overview, and Expert Case Studies

Land resources are central to understanding the relationship between humans and their environment. We broadly define a land resource to include all the ecological resources of climate, water, soil, landforms, flora, and fauna, and all the socioeconomic systems that interact with agriculture, forestry, and other land uses within some system boundary. Understanding the vulnerability of land resources to changes in land management or climate forcing is critical to developing sustainable land management strategies. Vulnerability assessments are complex given the multiple uses of the assessments, the multi-disciplinary nature of the problem, limited understanding, the dynamic structure of vulnerability, scale issues, and problems with identifying effective vulnerability indicators. Here, we propose a novel conceptual framework for vulnerability assessments of land resources that combines the driver– pressure–state–impact–response (DPSIR) framework adopted by the European Environment Agency to describe interactions between society and the environment, and the exposure-sensitivity-adaptive capacity (ESA) framework used by the Intergovernmental Panel on Climate Change to assess impacts of climate change. The DPSIR-ESA Vulnerability Assessment (DEVA) framework operationalizes the process of assessing the vulnerability of a target system to external stressors. The DEVA framework includes the following elements: 1) Definition of the target system (Land resource), 2) Description of internal characteristics of the target system (State), 3) Description of target system vulnerability indicators (Adaptive capacity, Sensitivity), 4) Description of stressor characteristics (Drivers, Pressures), 5) Description of stressor vulnerability indicators (Exposure), 6) Description of target system response to stressors (Impacts), and 7) Description of modifications to target systems or stressors (Responses). In stating that they have “applied the DEVA framework”, analysts acknowledge that they have (a) considered the full breadth of each DEVA element, (b) have made conscious decisions to limit the scope and complexity of certain elements, and (c) can communicate both the rationale for these decisions and the impact of these decisions on the vulnerability assessment results and recommendations. The DEVA framework was refined during invited presentations and follow-up discussions from a series of Special Sessions with leading experts at two successive ASABE Annual International Meetings. Six case studies drawn from the sessions elaborate upon the DEVA framework and provide concrete examples of the key concepts. The DEVA approach gives engineers, planners, and analysts a new, flexible framework to apply a broad array of useful tools toward assessment of land resource system vulnerability.

Anandhi, Aauvadi↗

Towards a Stronger Foundation: Digitizing Commercial Buildings with Brick to Enable Portable Advanced Applications

Most large commercial buildings have digital controls for their heating, ventilation, and air-conditioning (HVAC) and lighting systems with the potential to implement advanced control strategies and data analytics. However, advanced control strategies and data analytics are rarely deployed at scale due to non-standard naming conventions and heterogenous building configurations. Semantic metadata standards, like Brick, show promise to proliferate these applications across many buildings, but they have not been widely adopted by industry due to barriers such as perceived risk and unfamiliarity with the technology. This paper describes the workflow we established and evaluated while using it to develop over ten Brick models of existing buildings. Through this process, we observed that digitizing existing commercial buildings is a cost and labor-intensive effort in which understanding the buildings’ data streams is the major bottleneck. Yet, we conclude this investment is worthwhile since various use case applications such as fault detection and diagnostics, thermal comfort analysis, and HVAC control optimization can utilize the same Brick model. The paper also explores the challenges and lessons learned we encountered while creating these data models, such as: 1) difficulties in finding metadata descriptions and relationships for existing buildings; 2) handling missing concepts in the schema needed to model a building; 3) lack of guidance on how to structure the data model or how much detail to include; 4) unfamiliarity with technologies, which makes the learning curve steep for applications developers. Finally, we also describe future directions for semantic metadata research and development to make such transformative technologies more accessible to practitioners.

Roa, Carlos Duarte↗

Foundations to the unified psycho-cognitive engine.

This document outlines the key features of the SNL psychological engine. The engine is designed to be a generic presentation of cognitive entities interacting among themselves and with the external world. The engine combines the most accepted theories of behavioral psychology with those of behavioral economics to produce a unified simulation of human response from stimuli through executed behavior. The engine explicitly recognizes emotive and reasoned contributions to behavior and simulates the dynamics associated with cue processing, learning, and choice selection. Most importantly, the model parameterization can come from available media or survey information, as well subject-matter-expert information. The framework design allows the use of uncertainty quantification and sensitivity analysis to manage confidence in using the analysis results for intervention decisions.

99 GENERAL AND MISCELLANEOUS↗

Hygrothermal Simulation of Foundations: Part 1 - Soil Material Properties

The hygrothermal performance of soils coupled to buildings is a complicated process. A computational approach for heat transfer through the ground has been well defined (EN ISO 13370:2007, 2007), and simplified methods have been developed (Staszczuk, Radon, and Holm 2010). However, these approaches generally ignore the transfer of soil moisture, which is not negligible (Janssen, Carmeliet, and Hens 2004). This study is divided into several parts. The intention of the first part is to gather, comprehend and adapt soil properties from Soil Science. The obtained information must be applicable to related tasks in Building Science and validated with hygrothermal calculation tools. Future parts of this study will focus on the validation aspect of the soil properties to be implemented. Basic changes in the software code may be requested at this time. Different types of basement construction will be created with a hygrothermal calculation tool, WUFI. Simulations from WUFI will be compared with existing or ongoing measurements. The intentions of the first part of this study have been fulfilled. The soil properties of interest in Building Science have been defined for 12 different soil textures. These properties will serve as input parameters when performing hygrothermal calculations of building constructions coupled to soil materials. The reliability of the soil parameters will be further evaluated with measurements in Part 2.

Kehrer, Manfred↗

Foundations of Feature Selection and Classification for Non-Gaussian Distributed Targets

This report describes the author’s research toward creating algorithms for selecting useful statistical features in pattern/target classification problems in which the features are non-Gaussian distributed. In engineering practice, it is common to either (1) Not perform any feature selection procedure, or (2) Use a feature selection algorithm that assumes the features are Gaussian distributed. This process can be far from optimal if the data are actually non-Gaussian, as they frequently are in practice. This research has the goal of mitigating that problem by creating a useful algorithm that can be used in practice. The approach is to focus on the performance indices used in common feature selection algorithms, such as Branch and Bound algorithms and the Sequential Forward Selection Algorithm. Ordinarily, the performance index used to measure the class separation in feature space involves assuming the data are Gaussian and deriving tractable performance indices that use closed form equations that represent the probability density functions of the class data. The advantage of this approach is that it produces feature selection algorithms that have low computational complexity and do not require knowledge of the actual data densities. The disadvantage is that these algorithms may not perform reasonably when the data are non-Gaussian, as they commonly are in practice. This research examines the use of information-theoretic class separability measures that can deal with the non-Gaussian case. In particular, this work shows that the Hellinger Distance (a divergence measure), has very desirable mathematical properties and can be useful for feature selection. The work in this paper employs a multivariate kernel density estimator along with the Hellinger Distance and an optimal subset selection algorithm to do feature selection. This report (1) Defines the classification and feature selection problems, (2) Describes the continuous variable Hellinger distance in one dimension and discusses its mathematical properties in comparison with other distance measures, (3) Develops the discrete variable Hellinger distance expression for one and two dimensions, and shows that the discrete Hellinger distance for multiple dimensions is a straightforward extension, and (4) Presents experimental density estimation results using a new MATLAB implementation of a multivariate kernel density estimator. The draft of this report served as a starting point for Ensign Matthew Wilder’s MSEE thesis work at the Naval Postgraduate School (NPS) in 2010 and 2011. Ensign Wilder completed his thesis and graduated from NPS in June 2011 (M. J. Wilder, “Automatic Target Recognition: Statistical Feature Selection of Non-Gaussian Distributed Target Classes,” MSEE Thesis, Naval Postgraduate School, Thesis Advisor: Grace A. Clark, Second Reader: Monique P. Fargues, June 2011). In the thesis, Ensign Wilder created implementations of the Branch and Bound and Sequential Feature Selection algorithms, extended the multivariate kernel density estimator code, and evaluated the performance of Hellinger Distance-based feature selection algorithms using both simulated data and data from a real-world benchmark data set. The new algorithm was shown to be very effective for both Gaussian and non-Gaussian data sets. The advantages gained for non-Gaussian data come at the cost of increased computational complexity. Using a laptop computer for practical problems, we generally use initial feature vectors containing no more than about ten or twelve features. Proposed future research lies in creating faster kernel density estimator algorithms that would allow for the use of higher dimensional data.

42 ENGINEERING↗

Advanced Insulation for High Performance Cost-Effective Wall, Roof, and Foundation Systems Final Report

The objective of this project was to explore and potentially develop high performing insulation with increased R/inch and low impact on climate change that would help design highly insulating building envelope systems with more durable performance and lower overall system cost than envelopes with equivalent performance made with materials available today. The proposed technical approach relied on insulation foams with nanoscale pores (about 100 nm in size) in which heat transfer will be decreased. Through the development of new foaming methods, of new polymer formulations and new analytical techniques, and by advancing the understanding of how cells nucleate, expand and stabilize at the nanoscale, Dow successfully invented and developed methods to produce foams with 100 nm cells and 80% porosity by batch foaming at the laboratory scale. Measurements of the gas conductivity on small nanofoam specimen confirmed quantitatively the benefit of nanoscale cells (Knudsen effect) to increase insulation value, which was the key technical hypotheses of the program. In order to bring this technology closer to a viable semi-continuous/continuous process, the project team modified an existing continuous extrusion foaming process as well as designed and built a custom system to produce 6" x 6" foam panels. Dow demonstrated for the first time that nanofoams can be produced in a both processes. However, due to technical delays, foam characteristics achieved so far fall short of the 100 nm target set for optimal insulation foams. In parallel with the technology development, effort was directed to the determination of most promising applications for nanocellular insulation foam. Voice of Customer (VOC) exercise confirmed that demand for high-R value product will rise due to building code increased requirements in the near future, but that acceptance for novel products by building industry may be slow. Partnerships with green builders, initial launches in smaller markets (e.g. EIFS), and efforts to drive cost down will help acceptance in residential and commercial retrofit and new construction.

36 MATERIALS SCIENCE↗

Foundations for quantitative microstructural models to track evolution of the metallurgical state during high purity Nb cavity fabrication

The goal of the Materials Science SRF Cavity Group of Michigan State University and the National Superconducting Cyclotron has been (and continues to be) to understand quantitatively the effects of process history on functional properties. These relationships were assessed via studies on Nb samples and cavity parts, which had various combinations of forming processes, welding, heat treatments, and surface preparation. A primary focus was on large-grain cavity building strategies. Effects of processing operations and exposure to hydrogen on the thermal conductivity has been identified in single and bi-crystal samples, showing that the thermal conductivity can be altered by a factor of 5 depending on process history. Characterization of single crystal tensile samples show a strong effect of crystal orientation on deformation resistance and shape changes. Large grain half cells were examined to characterize defect content and surface damage effects, which provided quantitative information about the depth damage layers from forming.

43 PARTICLE ACCELERATORS↗

Foundational Tools for Petascale Computing

The Paradyn project has a history of developing algorithms, techniques, and software that push the cutting edge of tool technology for high-end computing systems. Under this funding, we are working on a three-year agenda to make substantial new advances in support of new and emerging Petascale systems. The overall goal for this work is to address the steady increase in complexity of these petascale systems. Our work covers two key areas: (1) The analysis, instrumentation and control of binary programs. Work in this area falls under the general framework of the Dyninst API tool kits. (2) Infrastructure for building tools and applications at extreme scale. Work in this area falls under the general framework of the MRNet scalability framework. Note that work done under this funding is closely related to work done under a contemporaneous grant, “High-Performance Energy Applications and Systems”, SC0004061/FG02-10ER25972, UW PRJ36WV.

97 MATHEMATICS AND COMPUTING↗

Theoretical foundation for measuring the groundwater age distribution.

In this study, we use PFLOTRAN, a highly scalable, parallel, flow and reactive transport code to simulate the concentrations of 3H, 3He, CFC-11, CFC-12, CFC-113, SF6, 39Ar, 81Kr, 4He and themean groundwater age in heterogeneous fields on grids with an excess of 10 million nodes. We utilize this computational platform to simulate the concentration of multiple tracers in high-resolution, heterogeneous 2-D and 3-D domains, and calculate tracer-derived ages. Tracer-derived ages show systematic biases toward younger ages when the groundwater age distribution contains water older than the maximum tracer age. The deviation of the tracer-derived age distribution from the true groundwater age distribution increases with increasing heterogeneity of the system. However, the effect of heterogeneity is diminished as the mean travel time gets closer the tracer age limit. Age distributions in 3-D domains differ significantly from 2-D domains. 3D simulations show decreased mean age, and less variance in age distribution for identical heterogeneity statistics. High-performance computing allows for investigation of tracer and groundwater age systematics in high-resolution domains, providing a platform for understanding and utilizing environmental tracer and groundwater age information in heterogeneous 3-D systems. Groundwater environmental tracers can provide important constraints for the calibration of groundwater flow models. Direct simulation of environmental tracer concentrations in models has the additional advantage of avoiding assumptions associated with using calculated groundwater age values. This study quantifies model uncertainty reduction resulting from the addition of environmental tracer concentration data. The analysis uses a synthetic heterogeneous aquifer and the calibration of a flow and transport model using the pilot point method. Results indicate a significant reduction in the uncertainty in permeability with the addition of environmental tracer data, relative to the use of hydraulic measurements alone. Anthropogenic tracers and their decay products, such as CFC11, 3H, and 3He, provide significant constraint oninput permeability values in the model. Tracer data for 39Ar provide even more complete information on the heterogeneity of permeability and variability in the flow system than the anthropogenic tracers, leading to greater parameter uncertainty reduction.

Gardner, William Payton↗

Final Report for Foundational Tools for Petascale Computing

This project concentrated on various aspects of creating tool infrastructure to make it easier to program large-scale parallel computers. This project was collaborative with the University of Wisconsin and closely related to the project DE-SC0002606 (“Tools for the Development of High Performance Energy Applications and Systems”) . The research conducted during this project is summarized in this report. The complete details of the work are available in the ten publications listed at the end of the report. Many of the concepts created during this project have been incorporated into tools and made available as freely downloadable software (at www.dyninst.org). It also supported the Ph.D. studies of three students and one research staff member.

97 MATHEMATICS AND COMPUTING↗

CS651 Computer Systems Security Foundations 3d Imagination Cyber Security Management Plan

3d Imagination is a new company that bases its business on selling and improving 3d open source related hardware. The devices that they sell include 3d imagers, 3d printers, pick and place machines and laser etchers. They have a fast company intranet for ease in sharing, storing and printing large, complex 3d designs. They have an employee set that requires a variety of operating systems including Windows, Mac and a variety of Linux both for running business services as well as design and test machines. There are a wide variety of private networks for testing transfer rates to and from the 3d devices, without interference with other network tra c. They do video conferencing conferencing with customers and other designers. One of their machines is based on the project found at delta.firepick.org(Krassenstein, 2014; Biggs, 2014), which in future, will perform most of those functions. Their devices all include embedded systems, that may have full blown operating systems. Most of their systems are designed to have swappable parts, so when a new technology is born, it can be quickly adopted by people with 3d Imagination hardware. This company is producing a fair number of systems and components, however to get the funding they need to mass produce quality parts, so they are preparing for an IPO to raise the funds they need. They would like to have a cyber-security audit performed so they can give their investors con dence that they are protecting their data, customers information and printers in a proactive manner.

97 MATHEMATICS AND COMPUTING↗

Foundational Report Series: Advanced Distribution Management Systems for Grid Modernization

This report describes the application functions for distribution management systems (DMS). The application functions are those surveyed by the IEEE Power and Energy Society’s Task Force on Distribution Management Systems. The description of each DMS application includes functional requirements and the key features and characteristics in current and future deployments, as well as a summary of the major benefits provided by each function to stakeholders — from customers to shareholders. Due consideration is paid to the fact that the realizable benefits of each function may differ by type of utility, whether investor-owned, cooperative, or municipal. This report is sufficient to define the functional requirements of each application for system procurement (request-for-proposal [RFP]) purposes and for developing preliminary high-level use cases for those functions. However, it should not be considered a design document that will enable a vendor or software developer to design and build actual DMS applications.

Wang, Jianhui↗