scholarly journals Evaluating Performance of Southern Ontario Buildings Using Submetering data and Whole Building Modeling Results

2021 ◽  
Author(s):  
Mark Adrian Turcato
Keyword(s):  
High Performance ◽  
Energy Use ◽  
Value Engineering ◽  
Data Sets ◽  
Performance Gap ◽  
Actual Performance ◽  
Energy Models ◽  
Building Modeling ◽  
Building Management ◽  
The Difference

The performance gap, the difference between how a building was intended to Perform and its actual performance, poses a challenge to successful high performance design. This research examines the application of submetering data and whole building energy models to evaluate the performance gap in buildings as related to energy consumption, and in specific energy use associated with receptacles and lighting. While difficulties in grappling with large amounts of data persist, results indicate that building management and occupancy issues can offer an explanation for a significant portion of differences between predicted and actual energy use. Experience working with these data sets also suggests that further efforts are required to demonstrate the value of submetering in order to ensure submetering systems are not compromised by the value engineering process.

scholarly journals Evaluating Performance of Southern Ontario Buildings Using Submetering data and Whole Building Modeling Results

2021 ◽  
Author(s):  
Mark Adrian Turcato
Keyword(s):  
High Performance ◽  
Energy Use ◽  
Value Engineering ◽  
Data Sets ◽  
Performance Gap ◽  
Actual Performance ◽  
Energy Models ◽  
Building Modeling ◽  
Building Management ◽  
The Difference

The performance gap, the difference between how a building was intended to Perform and its actual performance, poses a challenge to successful high performance design. This research examines the application of submetering data and whole building energy models to evaluate the performance gap in buildings as related to energy consumption, and in specific energy use associated with receptacles and lighting. While difficulties in grappling with large amounts of data persist, results indicate that building management and occupancy issues can offer an explanation for a significant portion of differences between predicted and actual energy use. Experience working with these data sets also suggests that further efforts are required to demonstrate the value of submetering in order to ensure submetering systems are not compromised by the value engineering process.

scholarly journals Closing the gap: an assessment of mixed-method data collection techniques in post occupancy evaluation

2021 ◽  
Author(s):  
Thomas Moore
Keyword(s):  
Data Collection ◽  
Mixed Method ◽  
High Performance ◽  
Energy Use ◽  
Predictive Performance ◽  
Practical Case ◽  
Performance Gap ◽  
Post Occupancy Evaluation ◽  
Energy Use Intensity ◽  
Performance Discrepancy

Demand for energy efficient buildings has supported an increase in predictive performance modeling. However, operation of buildings can often be different than predictive models, creating a collective performance discrepancy referred to as the “performance gap”. Post Occupancy Evaluation (POE) can close this gap by evaluating performance, and contrasting operational data to design intention. This POE demonstrates an identifiable performance gap in a practical case study on one high-performance building. Findings suggest the case building is not meeting anticipated energy consumption with a higher than predicted energy use intensity (EUI). Additional findings indicate a leaky building enclosure, significant thermal bridging, unrealistic simulation assumptions, acoustic disturbances, and occupant thermal comfort satisfaction. This POE demonstrates that mixed-method data collection provides more information than singular analyses when attempting to identify a performance gap. It is demonstrated that qualitative data collection techniques explain quantitative findings in analysis, informing understanding of performance gap causation.

scholarly journals Proteomic analysis of Nrk gene-disrupted placental tissue cells explains physiological significance of NRK

2019 ◽  
Vol 12 (1) ◽  
Author(s):  
Kimitoshi Denda ◽  
Kanako Ida ◽  
Masataka Tanno ◽  
Kanako Nakao-Wakabayashi ◽  
Masayuki Komada ◽  
...  
Keyword(s):  
High Performance ◽  
Gene Knockout ◽  
Expression Profiles ◽  
Placental Tissue ◽  
Data Sets ◽  
Wild Type ◽  
Two Dimensional Electrophoresis ◽  
The Difference ◽  
Protein Expression Profiles ◽  
Dimensional Electrophoresis

Abstract Objective NRK is a unique X chromosome-linked protein kinase expressed predominantly in placenta. The gene knockout causes placental overgrowth and delayed labor of Nrk-null fetuses from dams in mouse. To clarify unknown mechanisms behind the Nrk-null phenotypes, protein expression profiles were analyzed in the Nrk-null placenta using a high-performance two-dimensional electrophoresis methodology. Results Among around 1800 spots detected, we characterized a dozen protein spots whose expression levels were significantly altered in the Nrk-null placenta compared to wild-type. Analyzing these data sets is expected to reflect the difference physiologically in the presence or absence of NRK, facilitating the development of therapeutic strategies.

scholarly journals Analisis Biaya Pemeliharaan Bangunan Gedung Dengan Konsep Green building Dan Bangunan Gedung Dengan Konsep Non Green building

2021 ◽  
Vol 5 (3) ◽  
pp. 283-293
Author(s):  
Rika Apriani ◽  
Ida Ayu Ari Angreni
Keyword(s):  
High Performance ◽  
Green Building ◽  
Green Buildings ◽  
Public Works ◽  
Maintenance Costs ◽  
Large Company ◽  
Building Maintenance ◽  
Building Management ◽  
The Difference ◽  
The Cost

The concept of green building must also consider the cost of building maintenance in the post-construction stage so as not to reduce the large company costs each year. Green building is defined as a high-performance building that is made environmentally friendly, economically beneficial and healthy for life and workplace. This study intends to analyze the cost of building maintenance using the concept of green building non-green building. The data used in this study is the data on the maintenance costs of green buildings and non-green buildings. This data was taken by surveying the building management directly. Based on the analysis, the difference in the cost of maintaining green buildings and non-green buildings is Rp 10,283.22/m2/year. Based on the calculation, the maintenance costs of green building and non-green building still conform the standards of the Minister of Public Works Regulation and the standard of the Minister of Finance Regulation.

scholarly journals Closing the gap: an assessment of mixed-method data collection techniques in post occupancy evaluation

2021 ◽  
Author(s):  
Thomas Moore
Keyword(s):  
Data Collection ◽  
Mixed Method ◽  
High Performance ◽  
Energy Use ◽  
Predictive Performance ◽  
Practical Case ◽  
Performance Gap ◽  
Post Occupancy Evaluation ◽  
Energy Use Intensity ◽  
Performance Discrepancy

Demand for energy efficient buildings has supported an increase in predictive performance modeling. However, operation of buildings can often be different than predictive models, creating a collective performance discrepancy referred to as the “performance gap”. Post Occupancy Evaluation (POE) can close this gap by evaluating performance, and contrasting operational data to design intention. This POE demonstrates an identifiable performance gap in a practical case study on one high-performance building. Findings suggest the case building is not meeting anticipated energy consumption with a higher than predicted energy use intensity (EUI). Additional findings indicate a leaky building enclosure, significant thermal bridging, unrealistic simulation assumptions, acoustic disturbances, and occupant thermal comfort satisfaction. This POE demonstrates that mixed-method data collection provides more information than singular analyses when attempting to identify a performance gap. It is demonstrated that qualitative data collection techniques explain quantitative findings in analysis, informing understanding of performance gap causation.

Buildings

2017 ◽  
Author(s):  
Peter Rez
Keyword(s):  
Heat Transfer ◽  
Heat Pump ◽  
Energy Efficient ◽  
Energy Use ◽  
Fossil Fuel ◽  
Local Climate ◽  
Heating And Cooling ◽  
The Difference ◽  
As If

Most of the energy used by buildings goes into heating and cooling. For small buildings, such as houses, heat transfer by conduction through the sides is as much as, if not greater than, the heat transfer from air exchanges with the outside. For large buildings, such as offices and factories, the greater volume-to-surface ratio means that air exchanges are more significant. Lights, people and equipment can make significant contributions. Since the energy used depends on the difference in temperature between the inside and the outside, local climate is the most important factor that determines energy use. If heating is required, it is usually more efficient to use a heat pump than to directly burn a fossil fuel. Using diffuse daylight is always more energy efficient than lighting up a room with artificial lights, although this will set a limit on the size of buildings.

scholarly journals Statistical and machine learning models for optimizing energy in parallel applications

2019 ◽  
Vol 33 (6) ◽  
pp. 1079-1097 ◽  
Author(s):  
Mark Endrei ◽  
Chao Jin ◽  
Minh Ngoc Dinh ◽  
David Abramson ◽  
Heidi Poxon ◽  
...  
Keyword(s):  
Machine Learning ◽  
Energy Efficiency ◽  
High Performance ◽  
Large Scale ◽  
Energy Use ◽  
Parallel Applications ◽  
Learning Models ◽  
Trade Off ◽  
Time Required ◽  
Machine Learning Models

Rising power costs and constraints are driving a growing focus on the energy efficiency of high performance computing systems. The unique characteristics of a particular system and workload and their effect on performance and energy efficiency are typically difficult for application users to assess and to control. Settings for optimum performance and energy efficiency can also diverge, so we need to identify trade-off options that guide a suitable balance between energy use and performance. We present statistical and machine learning models that only require a small number of runs to make accurate Pareto-optimal trade-off predictions using parameters that users can control. We study model training and validation using several parallel kernels and more complex workloads, including Algebraic Multigrid (AMG), Large-scale Atomic Molecular Massively Parallel Simulator, and Livermore Unstructured Lagrangian Explicit Shock Hydrodynamics. We demonstrate that we can train the models using as few as 12 runs, with prediction error of less than 10%. Our AMG results identify trade-off options that provide up to 45% improvement in energy efficiency for around 10% performance loss. We reduce the sample measurement time required for AMG by 90%, from 13 h to 74 min.

scholarly journals The Mechanical Properties and Damage Evolution of UHPC Reinforced with Glass Fibers and High-Performance Polypropylene Fibers

Materials ◽  
2021 ◽  
Vol 14 (9) ◽  
pp. 2455
Author(s):  
Jiayuan He ◽  
Weizhen Chen ◽  
Boshan Zhang ◽  
Jiangjiang Yu ◽  
Hang Liu
Keyword(s):  
Mechanical Properties ◽  
Glass Fiber ◽  
Damage Evolution ◽  
High Performance ◽  
High Performance Concrete ◽  
Glass Fibers ◽  
Ultra High Performance Concrete ◽  
Concrete Damaged Plasticity ◽  
The Difference ◽  
Experimental Values

Due to the sharp and corrosion-prone features of steel fibers, there is a demand for ultra-high-performance concrete (UHPC) reinforced with nonmetallic fibers. In this paper, glass fiber (GF) and the high-performance polypropylene (HPP) fiber were selected to prepare UHPC, and the effects of different fibers on the compressive, tensile and bending properties of UHPC were investigated, experimentally and numerically. Then, the damage evolution of UHPC was further studied numerically, adopting the concrete damaged plasticity (CDP) model. The difference between the simulation values and experimental values was within 5.0%, verifying the reliability of the numerical model. The results indicate that 2.0% fiber content in UHPC provides better mechanical properties. In addition, the glass fiber was more significant in strengthening the effect. Compared with HPP-UHPC, the compressive, tensile and flexural strength of GF-UHPC increased by about 20%, 30% and 40%, respectively. However, the flexural toughness indexes I5, I10 and I20 of HPP-UHPC were about 1.2, 2.0 and 3.8 times those of GF-UHPC, respectively, showing that the toughening effect of the HPP fiber is better.

scholarly journals Managing energy performance in buildings from design to operation using modelling and calibration

2021 ◽  
pp. 014362442110083
Author(s):  
Nishesh Jain ◽  
Esfand Burman ◽  
Dejan Mumovic ◽  
Mike Davies
Keyword(s):  
Best Practice ◽  
Good Practice ◽  
Energy Performance ◽  
Operating Conditions ◽  
Design Stage ◽  
Performance Gap ◽  
Actual Performance ◽  
Simulation Tools ◽  
Calibration Protocol ◽  
Covering Design

To manage the concerns regarding the energy performance gap in buildings, a structured and longitudinal performance assessment of buildings, covering design through to operation, is necessary. Modelling can form an integral part of this process by ensuring that a good practice design stage modelling is followed by an ongoing evaluation of operational stage performance using a robust calibration protocol. In this paper, we demonstrate, via a case study of an office building, how a good practice design stage model can be fine-tuned for operational stage using a new framework that helps validate the causes for deviations of actual performance from design intents. This paper maps the modelling based process of tracking building performance from design to operation, identifying the various types of performance gaps. Further, during the operational stage, the framework provides a systematic way to separate the effect of (i) operating conditions that are driven by the building’s actual function and occupancy as compared with the design assumptions, and (ii) the effect of potential technical issues that cause underperformance. As the identification of issues is based on energy modelling, the process requires use of advanced and well-documented simulation tools. The paper concludes with providing an outline of the software platform requirements needed to generate robust design models and their calibration for operational performance assessments. Practical application The paper’s findings are a useful guide for building industry professionals to manage the performance gap with appropriate accuracy through a robust methodology in an easy to use workflow. The methodological framework to analyse building energy performance in-use links best practice design stage modelling guidance with a robust operational stage investigation. It helps designers, contractors, building managers and other stakeholders with an understanding of procedures to follow to undertake an effective measurement and verification exercise.

scholarly journals A Modified KNN Algorithm for High-Performance Computing on FPGA of Real-Time m-QAM Demodulators

Electronics ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 627
Author(s):  
David Marquez-Viloria ◽  
Luis Castano-Londono ◽  
Neil Guerrero-Gonzalez
Keyword(s):  
Real Time ◽  
High Performance ◽  
Interference Mitigation ◽  
Parallel Implementation ◽  
Computational Time ◽  
Successful Implementation ◽  
Interchannel Interference ◽  
The Difference ◽  
High Level ◽  
Performance Computing

A methodology for scalable and concurrent real-time implementation of highly recurrent algorithms is presented and experimentally validated using the AWS-FPGA. This paper presents a parallel implementation of a KNN algorithm focused on the m-QAM demodulators using high-level synthesis for fast prototyping, parameterization, and scalability of the design. The proposed design shows the successful implementation of the KNN algorithm for interchannel interference mitigation in a 3 × 16 Gbaud 16-QAM Nyquist WDM system. Additionally, we present a modified version of the KNN algorithm in which comparisons among data symbols are reduced by identifying the closest neighbor using the rule of the 8-connected clusters used for image processing. Real-time implementation of the modified KNN on a Xilinx Virtex UltraScale+ VU9P AWS-FPGA board was compared with the results obtained in previous work using the same data from the same experimental setup but offline DSP using Matlab. The results show that the difference is negligible below FEC limit. Additionally, the modified KNN shows a reduction of operations from 43 percent to 75 percent, depending on the symbol’s position in the constellation, achieving a reduction 47.25% reduction in total computational time for 100 K input symbols processed on 20 parallel cores compared to the KNN algorithm.

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