Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Comprehensive”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,315 records · Page 73
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Equilibrium carbon isotope fractionation factors of hydrocarbons: Semi-empirical force-field method

Here, we have calculated the reduced partition function ratios for carbon isotopes (β-factor) of 67 hydrocarbons (alkanes, alkenes, alkynes, cycloalkanes, and aromatics), including their 267 single-substituted isotopomers. The calculations were performed using the harmonic oscillator – rigid rotator model and the Urey / Bigeleisen-Mayer approach. Normal frequencies of molecular vibrations of the isotopologues were calculated from the molecular structures data and valence field force constants stored in the Light-handled Elucidation of Vibrations (LEV) database elaborated by Dr. Gribov and his colleagues in Russia. The LEV database is constructed from experimental spectroscopic and structural data by solving inverse problems of molecular vibrations. The LEV is internally consistent and the most comprehensive database available to date. The β-factor were calculated in the temperature range of 200–800 K with a 10 K step. Our calculations predict that the β-factors increase with an increasing number of C atoms within the same groups of hydrocarbons (e.g., alkanes). Our calculations also show a general descending order of 13 C enrichments among the different groups of hydrocarbons: cycloalkanes, aromatics, alkenes (double bonds) and isoalkanes, alkanes, alkynes (triple bonds). Position-specific, intramolecular isotope effects within hydrocarbons are determined by the β-factors of C in the different functional groups in the order: quaternary (C), tertiary (methine, CH), secondary (methylene, CH 2 ), primary (methyl, CH 3 ) and double bond (C=C), saturated bond (C - C), triple bond (HC≡). Our calculations on bulk and position-specific carbon isotope β-factors of the hydrocarbons, which are generally consistent with very limited ab initio calculations in the literature, are internally consistent and the most comprehensive to date for future applications to position-specific isotope geochemistry of hydrocarbons.

58 GEOSCIENCES↗
DOE OSTI2021

Discussion on molecular dynamics (MD) simulations of the asphalt materials

The application of asphalt materials in pavement engineering has been increasingly widespread and sophisticated over the past several decades. Variations in the properties of asphalt binder during mixing, transportation, and paving can affect the performance of asphalt pavement. However, the asphalt material is a non-homogeneous and complex organic substance, consisting of various molecules with widely various molecular weights, elemental compositions, and structures. This complexity leads to difficulties for researchers to clearly and immediately understand the properties of asphalt materials and their variations. The multi-scale research approach combines macroscopic experimental data and microscopic simulation results from a practical engineering perspective. It helps to improve the understanding of asphalt materials. The molecular dynamics (MD) simulation proposes a corresponding molecular model of asphalt material based on experimental data, and the simulation algorithm is able to derive properties similar to those of real asphalt. Here, this paper provides a comprehensive review of the current studies on MD simulation of asphalt materials, including modeling, properties, and multi-scale analysis. As a key part of the computational simulation, this paper discusses the typical asphalt binder and asphalt-aggregate interface models constructed by different groups, and also presents their differences from real samples and their feasibility based on fundamental properties. After the introduction of molecular models, the extensive work made by researchers based on molecular models is categorically reviewed and discussed. The strengths and weaknesses of MD simulation methods in the study of asphalt materials are also summarized in order to provide the reader with a more comprehensive understanding of the relevant contents and to guide subsequent research.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Comparative study of the counterflow forced ignition of the butanol isomers at atmospheric and elevated pressures

In support of the development of robust combustion models, the present study describes experimental and computational results on the non-premixed counterflow ignition of all four butanol isomers against heated air for pressures of 1–4 atm, pressure-weighted strain rates of 200–400 s -1 , and fuel molar fractions in nitrogen-diluted mixtures of 0.05–0.25. Comparison of the parametric effects of varied pressure, strain rate, and fuel loading among the isomers facilitates a comprehensive evaluation of the effect of varied structural isomerism on transport-affected ignition. The experimental findings are simulated using isomer-specific skeletal mechanisms developed from two comprehensive butanol models available in the literature, and are used to validate and assess the performance of these models. Comparison of the experimental and computational results reveal that while both models largely capture the trends in ignition temperature as functions of pressure-weighted strain rate, fuel loading, and pressure, for all isomers both models over-predict the experimental data to an appreciable extent. In addition, neither model captures the experimentally-observed ignition temperature rankings, with both models predicting a large spread among n-/iso-/sec-butanol which does not appear in the experimental results. Sensitivity and path analyses reveal that the butene isomers play a significant role in determining the ignition temperatures of the butanol isomers in both models, with the relative branching ratios likely accounting for the ignition temperature rankings observed using each model. It is observed that the reactivity of the butene isomers varies appreciably between the two butanol models, which may account for some of the variability in predictions between the two models. Moreover, effects of transport properties and their uncertainties on ignition temperature predictions are discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

High-throughput simulations for insight into grain boundary structure-property relationships and other complex microstructural phenomena

High-throughput simulations can be a powerful tool in the discovery of new materials and behaviors. As part of a special issue on Rising Stars in Computational Materials Science, this paper uses the work of the author to show how high-throughput simulations have had an impact in grain boundary structure-property relationships and other complex microstructural phenomena. The work demonstrates how new tools designed to analyze large datasets produced by high-throughput simulations are enabling comprehensive grain boundary structure-property relationships to be obtained. High-throughput simulations are also used to demonstrate the impact descriptive and inferential statistics has had in extracting key aspects of deformation in metallic glasses. Finally, several different examples are used to show a balanced approach between simulations designed to survey and simulations designed for detailed analysis. Together, the two approaches provide a comprehensive picture of the variety of behaviors that exist, while ensuring that the physics underlying the behaviors are thoroughly understood.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Large language model-driven database for thermoelectric materials

Thermoelectric materials have the ability to convert waste heat into electricity, offering a valuable solution for energy harvesting. However, their widespread use is hindered by low conversion efficiency, the reliance on expensive rare earth elements, and the environmental and regulatory concerns associated with lead-based materials. A fast and cost-effective way to identify highly efficient thermoelectric materials is through data-driven methods. These approaches rely on robust and comprehensive datasets to train models. Although there are several databases on thermoelectric materials, there is still a need to collect and integrate experimental data from peer-reviewed research articles to capture diverse compositions and properties of materials. Here, in this work, we developed a comprehensive database of 7,123 thermoelectric compounds, containing key information such as chemical composition, structural detail, seebeck coefficient, electrical and thermal conductivity, power factor, and figure of merit (ZT). We used the GPTArticleExtractor workflow, powered by large language models (LLM), to extract and curate data automatically from the scientific literature published in Elsevier journals. This process enabled the creation of a structured database that addresses the challenges of manual data collection. The open access database could stimulate data-driven research and advance thermoelectric material analysis and discovery.

Database↗
DOE OSTI2019

Revisiting the effects of molybdenum and tungsten alloying on corrosion behavior of nickel-chromium alloys in aqueous corrosion

Minor alloying additions such as molybdenum (Mo) have major effects on the localized corrosion resistance of corrosion resistant alloys containing chromium. However, progress in alloy development is mostly based upon empirical observations, where any mechanistic insights are largely relegated to the latter stages of localized corrosion (i.e., stabilization and propagation) that are more readily accessible experimentally. For instance, it is well understood that Mo and tungsten (W) affect repassivation of local active, as well as widespread transpassive, corrosion sites and Mo surface enrichment during corrosion is well-documented. In this paper, a comprehensive examination of the functions and mechanism by which selected Mo and W operate to improve the passivity and resistance to breakdown during the initial stages of localized corrosion of the most common Ni-based solid solution alloys is presented. Furthermore, it is shown that Mo and W exert considerable influence on many stages of corrosion, including both passivation and film breakdown, re-enforcing old and introducing more recent ideas in this comprehensive review of the current state of corrosion research on Ni-Cr-(Mo + W) alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2025

The Path towards Plasma Facing Components: A Review of State-of-the-art in W-Based Refractory High-Entropy Alloys

Developing advanced materials for plasma-facing components (PFCs) in fusion reactors is a crucial aspect for achieving sustained energy production. Tungsten (W) - based refractory high-entropy alloys (RHEAs) have emerged as promising candidates due to their superior radiation tolerance and high-temperature strength. This review paper will focus on recent advancements in W-based RHEA research, particularly emphasizing the key role of modelling using machine learning (ML) in the stage of discovery by predicting properties for each composition and expediting the identification of optimal RHEA compositions with desired properties. Additionally, the application of additive manufacturing (AM) techniques for fabricating W-based RHEAs is explored, highlighting their advantages for rapid prototyping and multi-compositional sample production in a high throughput manner. The review critically evaluates the current understanding of mechanical properties relevant to PFC applications, including high-temperature strength and ductility. Furthermore, the radiation tolerance of W-based RHEAs under irradiated conditions is discussed. Finally, the validity of current AM-manufactured W-based RHEAs as PFC materials is assessed, and key challenges and opportunities for future research are identified. This review aims to provide a comprehensive overview of W-based RHEAs for fusion applications and their potential to guide the development and validation of advanced refractory high entropy alloys.

Hatler, Caleb [University of Wisconsin-Madison]↗
DOE OSTI2025

Computational materials assessment of the D/Li-stripping neutron source as a prototypical facility for fusion materials testing

As the US fusion materials community awaits the selection and design of a fusion prototypical neutron source (FPNS), a risk reduction exercise has been conducted to (i) provide an updated materials performance evaluation using state-of-the-art computational materials modeling, (ii) expand on legacy analysis based on pure Fe to other relevant fusion structural materials types, and (iii) ensure that materials response under FPNS operational conditions is consistent with referential fusion reactor conditions. The current paper describes the efforts undertaken to assemble a comprehensive computational methodology that includes neutronics, primary damage calculations, atomistic simulations of displacement cascades, chemical inventory evolution calculations, and a computational thermodynamic analysis of emerging phases during irradiation. Our work extends existing studies in pure Fe to reduced-activation ferritic/martensitic steels, tungsten, silicon carbide, and vanadium alloys. We focus on the single-beam deuteron/lithium-stripping neutron source behind the IFMIF-DONES concept, which we assess against ITER, two DEMO designs, and an ideal pure 14-MeV flux. Our analysis indicates that, within standard uncertainties inherent to the models employed, the DONES concept adequately captures fusion conditions in the four materials analyzed. Our work is intended as a comprehensive irradiation damage analysis of fusion-representative neutron sources, to be used for further neutron source evaluation and fusion facility operation.

Marian, Jaime [Univ. of California, Los Angeles, C↗
DOE OSTI2022

Motif-centric phosphoproteomics to target kinase-mediated signaling pathways

Identifying cellular phosphorylation pathways based on kinase-substrate relationships is a critical step to understanding the regulation of physiological functions in cells. Mass spectrometry-based phosphoproteomics workflows have made it possible to comprehensively collect information on individual phosphorylation sites in a variety of samples. However, there is still no generic approach to uncover phosphorylation networks based on kinase-substrate relationships in rare cell populations. Here, we describe a motif-centric phosphoproteomics approach combined with multiplexed isobaric labeling, in which in vitro kinase reactions are used to generate targeted phosphopeptides, which are spiked into one of the isobaric channels to increase detectability. Proof-of-concept experiments demonstrate selective and comprehensive quantification of targeted phosphopeptides by using multiple kinases for motif-centric channels. More than 7,000 tyrosine phosphorylation sites were quantified from several tens of micrograms of starting materials. This approach enables the quantification of multiple phosphorylation pathways under physiological or pathological regulation in a motif-centric manner.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Towards the next generation of simplified Dark Matter models

Here this White Paper is an input to the ongoing discussion about the extension and refinement of simplified Dark Matter (DM) models. It is not intended as a comprehensive review of the discussed subjects, but instead summarises ideas and concepts arising from a brainstorming workshop that can be useful when defining the next generation of simplified DM models (SDMM). In this spirit, based on two concrete examples, we show how existing SDMM can be extended to provide a more accurate and comprehensive framework to interpret and characterise collider searches. In the first example we extend the canonical SDMM with a scalar mediator to include mixing with the Higgs boson. We show that this approach not only provides a better description of the underlying kinematic properties that a complete model would possess, but also offers the option of using this more realistic class of scalar mixing models to compare and combine consistently searches based on different experimental signatures. The second example outlines how a new physics signal observed in a visible channel can be connected to DM by extending a simplified model including effective couplings. In the next part of the White Paper we outline other interesting options for SDMM that could be studied in more detail in the future. Finally, we review important aspects of supersymmetric models for DM and use them to propose how to develop more complete SDMMs.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Innovations in underground hydrogen storage with multiphysics simulations, optimization, and monitoring: A review

Underground Hydrogen Storage (UHS) is a promising solution for large-scale energy storage and a critical component in advancing low-carbon energy system. Ensuring the safety and efficiency of UHS necessitates a comprehensive understanding of multiphysical interactions driven by cyclic pore fluid pressure fluctuations and coupled physicochemical processes. Here, this review examines the key geomechanical responses in UHS, including rock property variations under cyclic loading, fracture evolution and propagation, reservoir stress sensitivity, and fault stability. It also explores the impact of geochemical and microbial reactions on geomechanical characteristics. We provide an in-depth analysis of Thermal-Hydraulic-Mechanical-Chemical (THMC) coupled numerical simulations, highlighting their potential for future multi-scale modeling. Limitations of current machine learning (ML) approaches in addressing UHS challenges are highlighted, emphasizing the need for innovative ML-based methodologies. Operational strategies for hydrogen injection and production are reviewed, focusing on safety, efficiency, and economic viability. The necessity for multi-objective optimization (MOO) to balance storage efficiency, risk mitigation, and cost-effectiveness is also discussed. Current monitoring technologies are evaluated to ensure safe and efficient UHS operations. Finally, this review identifies critical knowledge gaps and underscores the importance of advancing geomechanical understanding under multiphysics-coupling. We highlight the need for ML-driven multiphysics theories, enhanced modeling techniques, and robust optimization strategies to improve UHS performance. This study serves as a comprehensive reference for future research and the large-scale implementation of UHS systems.

25 ENERGY STORAGE↗
DOE OSTI2025

Consistent performance of large language models in rare disease diagnosis across ten languages and 4917 cases

Background Large language models (LLMs) are increasingly used medicine for diverse applications including differential diagnostic support. The training data used to create LLMs such as the Generative Pretrained Transformer (GPT) predominantly consist of English-language texts, but LLMs could be used across the globe to support diagnostics if language barriers could be overcome. Initial pilot studies on the utility of LLMs for differential diagnosis in languages other than English have shown promise, but a large-scale assessment on the relative performance of these models in a variety of European and non-European languages on a comprehensive corpus of challenging rare-disease cases is lacking. Methods We created 4917 clinical vignettes using structured data captured with Human Phenotype Ontology (HPO) terms with the Global Alliance for Genomics and Health (GA4GH) Phenopacket Schema. These clinical vignettes span a total of 360 distinct genetic diseases with 2525 associated phenotypic features. We used translations of the Human Phenotype Ontology together with language-specific templates to generate prompts in English, Chinese, Czech, Dutch, French, German, Italian, Japanese, Spanish, and Turkish. We applied GPT-4o, version gpt-4o-2024-08-06, and the medically fine-tuned Meditron3-70B to the task of delivering a ranked differential diagnosis using a zero-shot prompt. An ontology-based approach with the Mondo disease ontology was used to map synonyms and to map disease subtypes to clinical diagnoses in order to automate evaluation of LLM responses. Findings For English, GPT-4o placed the correct diagnosis at the first rank 19.9% and within the top-3 ranks 27.0% of the time. In comparison, for the nine non-English languages tested here the correct diagnosis was placed at rank 1 between 16.9% and 20.6%, within top-3 between 25.4% and 28.6% of cases. The Meditron3 model placed the correct diagnosis within the first 3 ranks for 20.9% of cases in English and between 19.9% and 24.0% for the other nine languages. Interpretation The differential diagnostic performance of LLMs across a comprehensive corpus of rare-disease cases was largely consistent across the ten languages tested. This suggests that the utility of LLMs in clinical settings may extend to non-English clinical settings.

Artificial intelligence↗
DOE OSTI2024

Towards a liana plant functional type for vegetation models

Lianas (woody climbers) are crucial components of tropical forests and they have been increasingly recognized to have profound effects on tropical forest carbon dynamics. Despite their importance, lianas' representation in vegetation models remains limited, partly due to the complexity of liana-tree dynamics and the diversity in liana life history strategies. This paper provides a comprehensive review of advances and challenges for mechanistically representing lianas in forest ecosystem models and a proposed path towards effectively representing lianas in these models. Defining a liana plant functional type is a significant challenge because of the high morphological and physiological diversity amongst liana species, and because of their structural association with trees. Here, we identify critical liana traits that likely should contribute to establishing a liana plant functional type, along with key processes to properly represent lianas in ecosystem models. Subsequently, we discuss a variety of possible liana implementation strategies with their associated strengths, limitations, computational costs and data requirements. A fundamental redesign of the tree-centric demographic vegetation models seems appropriate to accommodate the unique growth and competition strategies of lianas. We illustrate the potential of such models with a single-site case study where we disentangle putative mechanisms of liana increasing abundance. Furthermore, we underscore the critical need for comprehensive liana demographic and functional data (including long-term, physiological, and pantropical observations) for the qualitative implementation and evaluation in the proposed modeling efforts. Currently, there is a scarcity of liana data and the data that do exist have a neotropical bias. We finally introduce a new liana functional trait database that can centralize existing liana trait data, incentivize improved data gathering and thus facilitate model development and scientific analyses.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Win-win transportation strategies for India: Linking air pollution and climate mitigation

Here, this article analyzes road transport in India to explore linkages between air pollution and climate change policies in the transportation sector. Five teams modeled five policy scenarios – fuel efficiency, electrification, alternative fuels, modal shifts, and moderation in transport demand – to explore which policy brings the largest synergetic effects in reducing carbon dioxide (CO 2 ) and particulate matter (PM 2.5 ) emissions. The teams also modeled the comprehensive scenario which included policy measures from individual scenarios. The paper concludes that all of the measures provide strong co-benefits in reducing air pollutant and CO 2 emissions. The modeling results show that increased energy efficiency of passenger and freight vehicles has the largest protentional for reducing both CO 2 and PM 2.5 emissions. It is possible to reach even a larger reduction of air pollutants and CO 2 emissions by combining several policy measures in the comprehensive scenario.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

The Modular Borehole Monitoring Program. A research program to optimize well-based monitoring for geologic carbon sequestration

Understanding the impacts caused by injection of large volumes of CO 2 in the deep subsurface necessitates a comprehensive monitoring strategy. While surface-based and other remote geophysical methods can provide information on the general morphology of a CO 2 plume, verification of the geochemical conditions and validation of the remote sensing data requires measurements from boreholes that penetrate the storage formation. Unfortunately, the high cost of drilling deep wellbores and deploying instrumentation systems constrains the number of dedicated monitoring borings as well as limits the technologies that can be incorporated in a borehole completion. The objective of the Modular Borehole Monitoring (MBM) Program was to develop a robust suite of well-based tools optimized for subsurface monitoring of CO 2 that could meet the needs of a comprehensive well-based monitoring program. It should have enough flexibility to be easily reconfigured for various reservoir geometries and geologies. The MBM Program sought to provide storage operators with a turn-key fully engineered design that incorporated key technologies, function over the decades long time-span necessary for post-closure reservoir monitoring, and meet industry acceptable risk profiles for deep-well installations. While still within the conceptual design phase of the MBM program, the SECARB Anthropogenic Test in Citronelle, Alabama, USA was identified as a deployment site for our engineered monitoring systems. The initial step in designing the Citronelle MBM system was to down-select from the various monitoring tools available to include technologies that we considered essential to any program. Monitoring methods selected included U-tube geochemical sampling, discrete quartz pressure and temperature gauges, an integrated fibre-optic bundle consisting of distributed temperature and heat-pulse sensing, and a sparse string of conventional 3C-geophones. While not originally planned within the initial MBM work scope, the fibre-optic cable was able to also be used for the emergent technology of distributed acoustic sensing. The MBM monitoring string was installed in March, 2012. To date, the Citronelle MBM instruments continue to operate reliably. Results and lessons learned from the Citronelle MBM deployment are addressed along with examples of data being collected.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Modelling the deployment of CO₂ storage in U.S. gas-bearing shales

The proliferation of commercial development in U.S. gas-bearing shales helped to drive a twelve-fold increase in domestic gas production between 2000 and 2010, and the nation's gas production rates continue to grow. While shales have long been regarded as a desirable caprock for CCS operations because of their low permeability and porosity, there is increasing interest in the feasibility of injecting CO₂ into shales to enhance methane recovery and augment CO₂ storage. Laboratory work published in recent years observes that shales with adsorbed methane appear to exhibit a stronger affinity for CO₂ adsorption, offering the potential to drive additional CH₄ recovery beyond primary production and perhaps the potential to store a larger volume of CO₂ than the volume of methane displaced. Recent research by the authors on the revenues associated with CO₂-enhanced gas recovery (CO₂-EGR) in gas-bearing shales estimates that, based on a range of EGR response rates, the average revenue per ton of CO₂ for projects managed over both EGR and subsequent storage-only phases could range from $0.50 to $18/tCO₂. While perhaps not as profitable as EOR, for regions where lower-cost storage options may be limited, shales could represent another “early opportunity” storage option if proven feasible for reliable EGR and CO₂ storage. Significant storage potential exists in gas shales, with theoretical CO₂ storage resources estimated at approximately 30-50 GtCO₂. However, an analysis of the comprehensive cost competitiveness of these various options is necessary to understand the degree to which they might meaningfully impact U.S. CCS deployment or costs. This preliminary analysis shows that the degree to which EGR-based CO₂ storage could play a role in commercial-scale deployment is heavily dependent upon the offsetting revenues associated with incremental recovery; modeling the low revenue case resulted in only five shale-based projects, while under the high revenue case, shales accounted for as much as 20 percent of total U.S. storage in the first 20 years of deployment. Interestingly, even in this highest revenue case, there appear to be no negative-cost projects that would be profitable in a no-policy environment as modeled under the assumptions employed. While this reflects a very first look at the potential for shales, it is clear that more laboratory and experimental work are needed to reduce uncertainty in key variables and begin to differentiate and identify high-potential shales for early pilot study.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Public participation in environmental impact assessment: why, who and how?

Even a cursory glance at the literature on environmental impact assessment (EIA) reveals that public participation is being considered as an integral part of the assessment procedure. Public participation in EIA is commonly deemed to foster democratic policy-making and to render EIA more effective. Yet a closer look at the literature unveils that, beyond this general assertion, opinions of the precise meaning, objectives and adequate representation of public participation in EIA considerably diverge. Against this background, in this article we aim to provide a comprehensive overview of the academic debate on public participation in EIA concerning its meaning, objectives and adequate level of inclusiveness. In so doing, we hope to stimulate a more focused debate on the subject, which is key to advancing the research agenda. Furthermore, this paper may serve as a starting point for practitioners involved in defining the role of public participation in EIA practice. -- Highlights: • There is little reflection on the meaning, objectives and adequate level of inclusiveness of public participation in EIA. • We provide a comprehensive overview of the academic debate on public participation in EIA concerning the meaning, objectives and adequate level of inclusiveness. • Theoretical claims put forth by scholars are contrasted with empirical evidence. • Overview shall stimulate a more focused debate on the subject. • This paper may serve as a starting point for practitioners involved in defining the role of public participation in EIA.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

A protocol for lifetime energy and environmental impact assessment of building insulation materials

This article describes a proposed protocol that is intended to provide a comprehensive list of factors to be considered in evaluating the direct and indirect environmental impacts of building insulation materials, as well as detailed descriptions of standardized calculation methodologies to determine those impacts. The energy and environmental impacts of insulation materials can generally be divided into two categories: (1) direct impact due to the embodied energy of the insulation materials and other factors and (2) indirect or environmental impacts avoided as a result of reduced building energy use due to addition of insulation. Standards and product category rules exist, which provide guidelines about the life cycle assessment (LCA) of materials, including building insulation products. However, critical reviews have suggested that these standards fail to provide complete guidance to LCA studies and suffer from ambiguities regarding the determination of the environmental impacts of building insulation and other products. The focus of the assessment protocol described here is to identify all factors that contribute to the total energy and environmental impacts of different building insulation products and, more importantly, provide standardized determination methods that will allow comparison of different insulation material types. Further, the intent is not to replace current LCA standards but to provide a well-defined, easy-to-use comparison method for insulation materials using existing LCA guidelines. - Highlights: • We proposed a protocol to evaluate the environmental impacts of insulation materials. • The protocol considers all life cycle stages of an insulation material. • Both the direct environmental impacts and the indirect impacts are defined. • Standardized calculation methods for the ‘avoided operational energy’ is defined. • Standardized calculation methods for the ‘avoided environmental impact’ is defined.

54 ENVIRONMENTAL SCIENCES↗