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At least 649 records · Page 36

Revisions to the SRCC Rating Process for Solar Water Heaters

In the United States, annual performance ratings for solar water heaters are computed with component-based simulation models driven by typical meteorological year weather and specified water draw. Changes in the process are being implemented to enhance credibility through increased transparency and accuracy. Changes to the process include using a graphical rather than text-based model-building tool, performing analytical tests on all components and systems, checking energy balances on every component, loop, and system at every time step, comparing the results to detect outliers and potential errors, and documenting the modeling process in detail. Examples of changes in ratings are shown, along with analytical and comparative testing results.

14 SOLAR ENERGY↗

Creating the Distributed Energy Resources Education Center (DEREC)

The built environment in the United States consumes 40% of the energy generated and emits roughly the same percentage of total carbon footprint. Distributed energy resources (DER), small or modular energy generation and storage technologies, present the nation with an opportunity to substantially improve those metrics while securing the nation’s energy independence. As opportunities increase for implementing such technologies, they also continue to evolve and often outpace the nation’s traditional building practices. In an effort to effectively and proactively incorporate distributed energy resources into the nation’s energy supply, Southface Energy Institute convened with national and regional partners to create the Distributed Energy Resources Education Center (DEREC). Using national model codes and their regionally amended versions as a collective starting point, the DEREC team collaborated with industry experts and identified impediments to effective implementation of DERs, developing discipline-specific curriculum to eliminate those impediments. The center, developed in collaboration with Interstate Renewable Energy Committee (IREC) and National Buildings Institute (NBI), leverages existing DER education content as well as new and dynamic training materials and online courses that collectively engage the many roles necessary for DER implementations, including designers, code officials, builders and skilled trades, and building owners who specify, inspect, build, operate, and maintain buildings with DERs.

14 SOLAR ENERGY↗

From Regolith to Living Off the Land: Formulating a Data Model to Catalog Lunar Construction Materials

Artemis Program objectives for sustainable, long-term presence on the Moon and more distant planetary surfaces will require learning to “Live off the Land”, relying on in-situ resource utilization to produce infrastructure and building materials from lunar regolith, icy subsurface deposits, and residual waste materials. Meeting demand for consumables while scaling development with resources found within the landing zone will require detailed data on the geology and environment of the lunar surface. Lunar infrastructure development will generate vast amounts of new engineering data regarding availability of processed feedstocks and their performance in building materials. Lunar engineering data accessible to program partners, research institutions and industry may help situate processes and specifications within the in-situ GIS context. Lunar missions to date have generated geological and ice favorability maps of the lunar surface, and recent technology studies have tested automated construction systems and novel material formulations using regolith simulants and binders. Current discussions focus on identifying key feedstocks, quantities required for nominal mission scenarios and infrastructure plans, and mapping the value chain from regolith to feedstock to consumables and construction materials.

lunar construction↗

From Regolith to Living Off the Land: Formulating a Data Model to Catalog Lunar Construction Materials

Artemis Program objectives for sustainable, long-term presence on the Moon and more distant planetary surfaces will require learning to “Live off the Land”, relying on in-situ resource utilization to produce infrastructure and building materials from lunar regolith, icy subsurface deposits, and residual waste materials. Meeting demand for consumables while scaling development with resources found within the landing zone will require detailed data on the geology and environment of the lunar surface. Lunar infrastructure development will generate vast amounts of new engineering data regarding availability of processed feedstocks and their performance in building materials. Lunar engineering data accessible to program partners, research institutions and industry may help situate processes and specifications within the in-situ GIS context. Lunar missions to date have generated geological and ice favorability maps of the lunar surface, and recent technology studies have tested automated construction systems and novel material formulations using regolith simulants and binders. Current discussions focus on identifying key feedstocks, quantities required for nominal mission scenarios and infrastructure plans, and mapping the value chain from regolith to feedstock to consumables and construction materials.

lunar construction↗

Sensor Data Management, Validation, Correction, and Provenance for Building Technologies

Oak Ridge National Laboratory (ORNL) conducts research on technologies that use a wide range of sensors to develop and characterize building energy performance. The management of high-resolution sensor data, analysis, and tracing lineage of such activities is challenging. Missing or corrupt data due to sensor failure, fouling, drifting, calibration error, or data logger failure is another issue. This paper focuses on sensor data management, validation, correction, and provenance to combat these issues, ensuring complete and accurate sensor datasets for building technologies applications and research. The design and development of two integrated software products are discussed: Sensor Data Validation and Correction (SensorDVC) and the Provenance Data Management System (ProvDMS) platform.

Data management↗

Envision Charlotte Project Final Report

The Envision Charlotte Project (EC Project), supported by partners at the Center for Climate and Energy Solutions, the University of North Carolina at Charlotte’s Center for Sustainably Integrated Buildings and Sites and the City of Charlotte, has successfully demonstrated that existing buildings can benefit from operations improvements and low-cost efficiency upgrades, and that behavioral change campaigns can be effectively designed for measurability, longevity and impact. Support from this grant gave Envision Charlotte and its partners the resources and flexibility to demonstrate a variety of approaches to improve coordination with stakeholders in the implementation of programs to reduce the consumption of energy, water and waste. The project team also gained insights into the motivations and abilities that influence stakeholder engagement in sustainability initiatives at multiple levels. Importantly, as this report describes, strong partnerships between nonprofits, industry partners and research institutions can produce tangible impacts and replicable results in building efficiency. Further, building operators working alongside student researchers can form productive relationships that can advance building energy management goals. Key Findings of the EC Project This project focused on advancing solutions to energy efficiency in U.S. commercial buildings. The Building Re-Tuning™ Training (BRT) developed by the U.S. DOE’s Pacific Northwest National Lab (PNNL), designed to detect energy savings opportunities and implement improvements with resources and online tools, provided the starting point for the curriculum developed by stakeholders in the EC Project. Although the project partners encountered some issues with data consistency, the overall project outcomes fell short of the energy savings stated in the original proposal, and the total participating building targets were lower than anticipated, important findings, outcomes and lessons learned were achieved. EC Project grantees observed that the PNNL BRT, as currently written, was not compatible with the skills of average frontline mechanical personnel in the Charlotte region where the grant program was performed. Frontline staff are not, typically, energy managers, engineers or building commissioning agents, but they can play a key role in building performance. As detailed in this report, the grantees therefore focused on changes to the BRT that improved the level of training and competency of the frontline workers in this region. Among the technical observations related to improving the BRT that were observed in the EC Project: centralized facilities management often has an impact on building performance; operators can be overly reliant on service contracts; individual behaviors matter, and technology cannot be viewed as a crutch; current Building Automation Systems (BAS) are often too complex to support building efficiency optimization, but BAS coupled with appropriate training can support better outcomes; the “perfectly optimized” building is not a near-term possibility, but better education, especially of executives and managers, on the role of behavioral intervention is a promising direction the building science community can and should pursue; a lack of standards and protocols, and competition between proprietary software from service contracts, remain challenges for this industry. These technical observations, in turn, informed the EC Project’s overall findings, which were: Accomplishing building efficiency is a process of education for all involved in the building design, construction and operation supply chain. Building operators, as a professional class, have an opportunity for further training and education that will lead to better on-the-job performance. An updated Building Re-Tuning™ Training curriculum, based on the findings of this report, could be an avenue for these operators’ professional development.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Advanced Envelope Research for Factory Built Housing, Phase 3 - Whole-House Prototyping

The Advanced Envelope Research effort will provide factory homebuilders with high performance, cost-effective envelope designs that can be effectively integrated into the plant production process while meeting the thermal requirements of the 2012 IECC standards. Given the affordable nature of manufactured homes, impact on first cost is a major consideration in developing new envelope technologies. This work is part of a multi-phase effort. Phase 1 identified seven envelope technologies and provided a preliminary assessment of three methods for building high performance walls. Phase 2 focused on developing viable product designs, manufacturing strategies, addressing code and structural issues, and cost analysis of the three selected options. An industry advisory committee helped narrow the research focus to perfecting a stud wall design with exterior continuous insulation (CI). Phase 3, completed in two stages, continued the design development effort, exploring and evaluating a range or methods for applying CI to factory built homes. The scope also included material selection, manufacturing and cost analysis, and prototyping and testing. During this phase, a home was built with CI, evaluated, and placed in service. The experience of building a mock up wall section with CI and then constructing on line a prototype home resolved important concerns about how to integrate the material into the production process. First steps were taken toward finding least expensive approaches for incorporating CI in standard factory building practices and a preliminary assessment suggested that even at this early stage the technology is attractive when viewed from a life cycle cost perspective.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Coupling multi-fidelity xRAGE with machine learning for graded inner shell design optimization in double shell capsules

Bayesian optimization has shown promise for the design optimization of inertial confinement fusion targets. Specifically, in Vazirani et al. [Phys. Plasmas 28 , 122709 (2021)], optimal designs for double shell capsules with graded inner shells were identified using one-dimensional xRAGE simulation yield calculations. While the machine learning models were able to accurately learn and predict one-dimensional simulation target performance, using simulations with higher fidelity would improve design optimization and better match with the expected experimental performance. However, higher fidelity physics modeling, i.e., two-dimensional xRAGE simulations, requires significantly larger computational time/cost, usually at least an order of magnitude, in comparison with one-dimensional simulations. This study presents a multi-fidelity Bayesian optimization, in which the machine learning model leverages low-fidelity (one-dimensional xRAGE) and high-fidelity (two-dimensional xRAGE) simulations to more accurately predict “pre-shot” target performance with respect to the expected experimental performance. By building a multi-fidelity Bayesian optimization framework coupled with xRAGE, the low-fidelity and high-fidelity simulations are able to inform one another, such that we have: (1) improved physics modeling in comparison with using low-fidelity simulations alone, (2) reduced computational time/cost in comparison with using high-fidelity simulations alone, and (3) more confidence in the expected performance of optimized targets during real-world experiments. In the future, we plan to use this robust multi-fidelity Bayesian optimization methodology to expedite the design of graded inner shells further and eventually full capsules as a part of the current double shell campaign at the National Ignition Facility.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Roof-integrated radiative air-cooling system to achieve cooler attic for building energy saving

The building attic usually subjects to substantial solar heat gain and has much higher temperature compared to the conditioned living space during the day, especially in summer and in hot areas. Reducing attic temperature can reduce cooling energy consumption in buildings. However, conventional techniques such as cool roof or attic ventilation, suffer from either heating penalty in winter or limited attic temperature reduction. In this work, a new roof-integrated radiative air-cooling system is introduced, which couples radiative sky cooling with attic ventilation to reduce attic temperature. A radiative air cooler with 1.08 m 2 surface area is constructed using a recently developed daytime radiative sky cooling metamaterial [Zhai et al., Science 355, pp. 1062–1066, 2017]. Experimental tests show that sub-ambient air cooling is achieved throughout 24-h day-and-night cycle in a summer day with clear sky conditions. Depending on air flow rates, measured sub-ambient temperature reductions of air are 5–8°C at night and 3–5°C at noon under direct sunlight, respectively. An in-house model is first developed for the radiative air-cooling system, the model is then coupled with EnergyPlus to study annual energy saving of buildings. The performance of the radiative air-cooling system is compared with three reference systems: shingle roof, attic ventilation, and cool roof. Results show that for a single-family house, attic temperature can be substantially reduced by 15.5–21.0°C, varying with attic insulation level, compared to shingle roof on typical summer days. Compared to a shingle roof (solar reflectance 0.25, thermal emittance 0.9) residential building with attic insulations of R-30 (RSI-5.28), R-10 (RSI-1.76), and R-0.8 (RSI-0.14), the roof-integrated radiative air-cooling system can achieve annual cooling energy savings of 0.4–1.5 kWh/m 2 (4.6–18.8%), 1.2–3.6 kWh/m 2 (10.2–41.4%), and 3.7–11.8 kWh/m 2 (26.5–76.1%) respectively.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

A dataset for understanding self-reported patterns influencing residential energy decisions

Household occupant behavior and decision-making dynamics substantially impact technology uptake and residential building energy performance. Although significant research underscores the importance of social science in energy studies, few public data with representative samples on household energy decision-making patterns are available. The dataset (UPGRADE-E: Understanding Patterns Guiding Residential Adoption and Decisions about Energy Efficiency) presents 9,919 responses from U.S. residents of single-family and small multifamily homes. Derived from a national-scale internet survey, the dataset contains 391 variables: demographics, building characteristics, home modifications, willingness to adopt new technologies, motivations for making changes, barriers, program participation, trusted information sources, and energy scenarios. Responses were validated via internal consistency checks and comparison with other U.S. national scale datasets. UPGRADE-E advances knowledge of household energy related decision-making, tying demographics, home modifications, and self-reported cognitive drivers together at a scale and breadth that has not been previously achieved. Policymakers and researchers at local, regional, and national levels may leverage this dataset to understand drivers influencing the adoption of key technologies in U.S. homes.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Laboratory Efficiency Strategies and the Smart Labs Program

Focusing on critical spaces, such as labs, will enable agencies to prioritize federal energy efficiency and decarbonization goals. FEMP's Smart Labs program is an example of emerging efficient laboratory building strategies. The benefits of this program include improved safety and health, reduced energy consumption and carbon emissions, lower operating costs, reduced degradation, and increased retention and recruitment of top talent researchers and sciences. In this session, with the help of our national lab partners, Sandia National Laboratory and Lawrence Berkeley National Laboratory, you will learn about the steps to implement a Smart Labs program of your own and the methods behind the high-performance laboratory building. The partners will share best practices in implementation, practical advice for building a team, and how to address these critical facilities.

decarbonization↗

A novel Variable Refrigerant Flow (VRF) heat recovery system model: Development and validation

As one of the latest emerging HVAC technologies, the Variable Refrigerant Flow (VRF) system with heat recovery (HR) configurations has obtained extensive attention from both the academia and industry. Compared with the conventional VRF systems with heat pump (HP) configurations, VRF-HR is capable of recovering heat from cooling zones to heating zones and providing simultaneous cooling and heating operations. Moreover, this could lead to substantial energy saving potential and more flexible zonal control. In this paper, a novel model is developed to simulate the energy performance of VRF-HR systems. It adheres to a more physics-based development with the ability to simulate the refrigerant loop performance and consider the dynamics of more operational parameters, which is crucial for representing more advanced control logics. Another key feature of the model is the introduction of component-level curves for indoor units and outdoor units instead of overall performance curves for the entire system, and thus it requires much fewer user-specified performance curves as model inputs. The validation study reflects good agreements between the simulated energy use from the new VRF-HR model and the laboratory measurement data across all operational modes at sub-hourly time steps. The model has been adopted in the official release of the EnergyPlus simulation program since Version 8.6, which enables more accurate and robust assessments of VRF-HR systems to support their applications in energy retrofit of existing buildings or design of zero-net-energy buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Effect of processing parameters and build orientation on microstructure and performance of AISI stainless steel 304L made with selective laser melting under different strain rates

Selective laser melting (SLM) process brings diverse potentials on geometry flexibility; therefore, it is more and more widespread to be employed in fabrication metal alloys served for industries. Nonetheless, a material characterization study is desired to carry on for better understanding the correlation among process, structure, microstructure, and performance. In the current study, the SLM fabricated AISI stainless steel 304L was fabricated with different process parameters and built orientations (horizontal, inclined, and vertical. The tensile behavior was evaluated under different strain rates (0.0001 /s, 0.001 /s, 0.01 /s, and 0.1 /s) and compared to the commercial cold-rolled and annealed counterpart. Grain structures, tensile strength, elongation-to-failure, strain rate sensitivity, work hardening, and fractographic analysis were evaluated in terms of the effect of energy density, build orientation, and strain rate. The output indicates the tensile strength increases with increasing strain rates. On the contrary, the elongation-to-failure shows a decreasing trend with strain rates. Tensile properties of specimens built in the horizontal and inclined orientations are more sensitive to strain rates due to the smaller dimension of grain structures. Tensile anisotropy depends on the energy input, where a high energy density could yield a strong build orientation-dependent anisotropy. Hall-Petch relationship is validated to explain the mechanical anisotropy in different built orientations for SLM alloys. The strain hardening exponent and work hardening rate are demonstrated to be positively correlated, and they increase with smaller grain sizes. The fine dimple features indicate the ductile fracture mode regardless of strain rates. The size of the ductile dimples seems to depend on the strain rates and build orientations.

36 MATERIALS SCIENCE↗

Whole-building life-cycle analysis with a new GREET® tool: Embodied greenhouse gas emissions and payback period of a LEED-Certified library

Embodied greenhouse gas (GHG) emissions of building components and buildings operations need to be quantified to holistically address building sustainability. To evaluate embodied GHG emissions of buildings and to provide insights on building materials and building design decisions toward decarbonization, we have recently created a building life-cycle assessment (LCA) module in the widely used Greenhouse gases, Regulated Emissions, and Energy use in Technologies (GREET (R)) LCA model. We applied the GREET building LCA module to examine embodied GHG impacts and the payback period of a LEED (Leadership in Energy and Environmental Design) certified public library in Chicago, USA. We developed localized, detailed life-cycle inventories to address individual building materials used in the library. We expanded the LCA system boundary to include the mechanical, electrical, and plumbing system, as well as refrigerant impacts, which are often ignored in previous studies. Results show that the total embodied GHG emissions are approximately 817 metric tons, or approximately 538 kg/m 2 . Sensitivity analysis highlights the positive role of increasing the use of recycled materials for reducing embodied GHG emissions. Sensitivity analysis on embodied GHG emissions payback periods shows the need to benchmark the embodied and operational carbon performance of buildings for comparison to alternative building designs and sustainability practices. Furthermore, this analysis demonstrates that building LCA models, such as the GREET building LCA module, which addresses embodied and operational GHG emission impacts of whole buildings holistically, could empower building architects, technology developers, manufacturers, and general contractors to address embodied and operational impacts holistically for building sustainability.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Rooftop unit comparison calculator: a framework for comparing performance of rooftop units with building energy simulation

The applications of building energy simulation (BES) in designing heating, ventilation, and air conditioning (HVAC) systems are limited by the high costs of developing simulation models and the lack of references for determining the model parameters. This paper presents a software framework for selecting designs for rooftop unit HVAC (RTU) systems with BES. Specifically, this framework reduces the cost of using BES by automating the generation of EnergyPlus models. It also employs a systematic method for determining model parameters based on well-accepted datasets. We applied this framework in a comprehensive assessment of an advanced design of RTU systems in which 478 EnergyPlus models were developed without human involvement. The assessment reveals that replacing a constant-speed fan/coil with a multiple-speed fan/coil may not guarantee better overall performance. In conclusion, it also suggests the benefits of replacing furnace coils with heat pumps are subject to utility cost, weather conditions, and heating load profiles.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Expert Meeting Report: Foundations Research Results

In the Expert Meeting Plan, the NorthernSTAR Team proposed to host two Expert Meetings in calendar year 2011. Invitees to the meetings would include experts in the current field of study, other BA team members, and representatives from DOE and NREL. They will invite leading industry experts to present at these meetings. The Expert Meetings will focus on key systems areas that will be required to meet the Building America performance goals and shall be sufficiently narrow in scope that specific conclusions, action items, and delegation of future tasks can be identified and completed. The two expert meeting topics are 'Foundations' and 'Window Retrofit.' The first session is designed as a webinar only and the second will be a live meeting.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗