FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4317505550> ?p ?o ?g. }

• W4317505550 endingPage "1920" @default.
• W4317505550 startingPage "1920" @default.
• W4317505550 abstract "Recent developments in dynamic energy simulation tools enable the definition of energy performance in buildings at the design stage. However, there are deviations among building energy simulation (BES) tools due to the algorithms, calculation errors, implementation errors, non-identical inputs, and different weather data processing. This study aimed to analyze several building energy simulation tools modeling the same characteristic office cell and comparing the heating and cooling loads on a yearly, monthly, and hourly basis for the climates of Boston, USA, and Madrid, Spain. First, a general classification of tools was provided, from basic online tools with limited modeling capabilities and inputs to more advanced simulation engines. General-purpose engines, such as TRNSYS and IDA ICE, allow users to develop new mathematical models for disruptive materials. Special-purpose tools, such as EnergyPlus, work with predefined standard simulation problems and permit a high calculation speed. The process of reaching a good agreement between all tools required several iterations. After analyzing the differences between the outputs from different software tools, a cross-validation methodology was applied to assess the heating and cooling demand among tools. In this regard, a statistical analysis was used to evaluate the reliability of the simulations, and the deviation thresholds indicated by ASHRAE Guideline 14-2014 were used as a basis to identify results that suggested an acceptable level of disagreement among the outcomes of all models. This study highlighted that comparing only the yearly heating and cooling demand was not enough to find the deviations between the tools. In the annual analysis, the mean percentage error values showed a good agreement among the programs, with deviations ranging from 0.1% to 5.3% among the results from different software and the average values. The monthly load deviations calculated by the studied tools ranged between 12% and 20% in Madrid and 10% and 14% in Boston, which were still considered satisfactory. However, the hourly energy demand analysis showed normalized root mean square error values from 35% to 50%, which were far from acceptable standards." @default.
• W4317505550 created "2023-01-20" @default.
• W4317505550 creator A5001142377 @default.
• W4317505550 creator A5026546985 @default.
• W4317505550 creator A5039092859 @default.
• W4317505550 date "2023-01-19" @default.
• W4317505550 modified "2023-10-05" @default.
• W4317505550 title "Assessment of Building Energy Simulation Tools to Predict Heating and Cooling Energy Consumption at Early Design Stages" @default.
• W4317505550 cites W1542463634 @default.
• W4317505550 cites W1999979720 @default.
• W4317505550 cites W2019623686 @default.
• W4317505550 cites W2029463080 @default.
• W4317505550 cites W2038916100 @default.
• W4317505550 cites W2064875688 @default.
• W4317505550 cites W2108152153 @default.
• W4317505550 cites W2128120029 @default.
• W4317505550 cites W2203837178 @default.
• W4317505550 cites W2750684196 @default.
• W4317505550 cites W2791300204 @default.
• W4317505550 cites W2952570290 @default.
• W4317505550 cites W2957724442 @default.
• W4317505550 cites W2971781381 @default.
• W4317505550 cites W2990899769 @default.
• W4317505550 cites W3000984364 @default.
• W4317505550 cites W3025783071 @default.
• W4317505550 cites W3108502061 @default.
• W4317505550 cites W3137837648 @default.
• W4317505550 cites W3180353127 @default.
• W4317505550 cites W3183082633 @default.
• W4317505550 cites W4214866555 @default.
• W4317505550 cites W4221108045 @default.
• W4317505550 cites W4286750222 @default.
• W4317505550 cites W4291298116 @default.
• W4317505550 cites W4297538801 @default.
• W4317505550 cites W4300972011 @default.
• W4317505550 cites W758726060 @default.
• W4317505550 doi "https://doi.org/10.3390/su15031920" @default.
• W4317505550 hasPublicationYear "2023" @default.
• W4317505550 type Work @default.
• W4317505550 citedByCount "8" @default.
• W4317505550 countsByYear W43175055502023 @default.
• W4317505550 crossrefType "journal-article" @default.
• W4317505550 hasAuthorship W4317505550A5001142377 @default.
• W4317505550 hasAuthorship W4317505550A5026546985 @default.
• W4317505550 hasAuthorship W4317505550A5039092859 @default.
• W4317505550 hasBestOaLocation W43175055501 @default.
• W4317505550 hasConcept C105795698 @default.
• W4317505550 hasConcept C108215451 @default.
• W4317505550 hasConcept C111919701 @default.
• W4317505550 hasConcept C119599485 @default.
• W4317505550 hasConcept C121332964 @default.
• W4317505550 hasConcept C127413603 @default.
• W4317505550 hasConcept C13736549 @default.
• W4317505550 hasConcept C149808339 @default.
• W4317505550 hasConcept C153294291 @default.
• W4317505550 hasConcept C162324750 @default.
• W4317505550 hasConcept C175444787 @default.
• W4317505550 hasConcept C186370098 @default.
• W4317505550 hasConcept C199360897 @default.
• W4317505550 hasConcept C200601418 @default.
• W4317505550 hasConcept C206145494 @default.
• W4317505550 hasConcept C2776409380 @default.
• W4317505550 hasConcept C2777904410 @default.
• W4317505550 hasConcept C2778457487 @default.
• W4317505550 hasConcept C2780165032 @default.
• W4317505550 hasConcept C2982928256 @default.
• W4317505550 hasConcept C33923547 @default.
• W4317505550 hasConcept C41008148 @default.
• W4317505550 hasConcept C44154836 @default.
• W4317505550 hasConcept C91757755 @default.
• W4317505550 hasConcept C98045186 @default.
• W4317505550 hasConceptScore W4317505550C105795698 @default.
• W4317505550 hasConceptScore W4317505550C108215451 @default.
• W4317505550 hasConceptScore W4317505550C111919701 @default.
• W4317505550 hasConceptScore W4317505550C119599485 @default.
• W4317505550 hasConceptScore W4317505550C121332964 @default.
• W4317505550 hasConceptScore W4317505550C127413603 @default.
• W4317505550 hasConceptScore W4317505550C13736549 @default.
• W4317505550 hasConceptScore W4317505550C149808339 @default.
• W4317505550 hasConceptScore W4317505550C153294291 @default.
• W4317505550 hasConceptScore W4317505550C162324750 @default.
• W4317505550 hasConceptScore W4317505550C175444787 @default.
• W4317505550 hasConceptScore W4317505550C186370098 @default.
• W4317505550 hasConceptScore W4317505550C199360897 @default.
• W4317505550 hasConceptScore W4317505550C200601418 @default.
• W4317505550 hasConceptScore W4317505550C206145494 @default.
• W4317505550 hasConceptScore W4317505550C2776409380 @default.
• W4317505550 hasConceptScore W4317505550C2777904410 @default.
• W4317505550 hasConceptScore W4317505550C2778457487 @default.
• W4317505550 hasConceptScore W4317505550C2780165032 @default.
• W4317505550 hasConceptScore W4317505550C2982928256 @default.
• W4317505550 hasConceptScore W4317505550C33923547 @default.
• W4317505550 hasConceptScore W4317505550C41008148 @default.
• W4317505550 hasConceptScore W4317505550C44154836 @default.
• W4317505550 hasConceptScore W4317505550C91757755 @default.
• W4317505550 hasConceptScore W4317505550C98045186 @default.
• W4317505550 hasIssue "3" @default.
• W4317505550 hasLocation W43175055501 @default.

• next