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Summary
Building stakeholders need practical information that aids long-term capital investment decisions related to building designs and technologies. This project addresses these needs through standards-based performance data, metrics, and tools for building systems and whole buildings. It is focused on life cycle analysis of building construction and operation using Life-Cycle Cost Analysis (LCCA) and Life-Cycle Assessment (LCA) combined with dynamic operational performance modeling to account for the integrated nature of building systems and impacts on occupants. Recently, this project has prioritized developing a modularized web Application Programming Interface (API) that is interoperable with existing and new software to assist technical audiences in incorporating standards-based life cycle analysis into other platforms. The Economic Evaluation Engine (E3) provides topic-agnostic ASTM standards-based economic analysis of engineered systems that facilitate development of user applications across multiple research areas within the Engineering Laboratory (EL) at NIST. Decision support tools Powered by E3 have now been released. Additionally, this project has coordinated with other federal agencies through the Federal LCA Commons and the LCA community to pursue activities to enhance standardization in LCA data and modeling to increase accuracy, transparency, comparability, and interoperability in LCA modeling of building materials, building systems, and whole buildings.
Description
Objective
To develop and deploy transparent, open source standards-based data and tools that quantify the life-cycle performance of building technologies and systems through parallel activities focused on developing, releasing, and expanding capabilities and adoption of: (1) the Economic Evaluation Engine (E3) web API that is interoperable with other software, (2) web applications leveraging E3 to provide decision support for stakeholders, and (3) LCA-related standards and datasets to address the needs of standards development organizations (SDOs), the LCA Community (i.e., American Center for Life Cycle Assessment – ACLCA) and other federal agencies (i.e., Federal LCA Commons -FLCAC).
Technical Idea
To develop, release, and disseminate standards-based information, data, metrics, and tools to improve capital asset investment choices and decision-making related to high performing building designs and technologies. This project focuses on life cycle analysis of the economics and multi-objective optimization of building construction and operation using LCCA and LCA considering the integrated nature of building systems and impacts on occupants.
Prior research included the development of support tools that focused on the needs of a range of technical and non-technical stakeholders in making capital asset investment decisions in the buildings and infrastructure at the product, system, and whole building levels. More recently, this project has transitioned its focus onto data and model development as well as modularization and interoperability of life cycle analysis tools that allow for inclusion of multi-objective criteria and metrics in other building-related decision tools without the need for extensive expertise.
E3 is a topic-agnostic economic analysis tool for engineered systems. The E3 API provides multiple economic analysis capabilities in a consistent format using ASTM standards. E3 provides a range of economic evaluation capabilities, including LCCA, benefit-cost analysis (BCA), profit maximization, monetary and non-monetary trade-off analysis, sensitivity testing, and uncertainty analysis. E3 is expected to streamline the development of future economic analysis tools developed by AEO as demonstrated by E3’s three initial use cases: [PV]2, SITExpress, and Building Life Cycle Cost (BLCC). E3 is also being used through direct request for economic analysis research in EL. E3 can be leveraged by other NIST researchers as well as by external stakeholders to evaluate topic areas across NIST goals and programs.
In addition to economic tool development, this project is collaborating with ASTM, ACLCA, and the FLCAC federal agency members to identify standards and data needs that must be addressed and develop tools to improve the quality, transparency, and comparability of building product and system LCAs. These include template LCA models and public data gap assessments of select construction materials and building systems. Additionally, a support tool leveraging AI is being developed to assist in standardizing and digitizing environmental product declarations (EPDs) called ParsEPD.
Research Plan
The key decision-support tool developed under this project is the Economic Evaluation Engine (E3), which is an API that provides an array of economic evaluation methodologies based on ASTM standards, including LCCA and BCA as well as sensitivity and uncertainty analysis. By design the E3 API allows any software tool (e.g., script, executable, web interface) to call on the API and ensure the calculations are providing standards-based results. The initial tool Powered by E3 is Present Value of PhotoVoltaics ([PV]2), which is a web application that allows homeowners to determine a complete cost of ownership for residential rooftop solar photovoltaic (PV) systems including purchase and operation through the system’s service life as well as consideration of other non-economic performance relative to consuming energy from the electric grid. E3 support resources include “how to” documentation on leveraging E3 for building web applications, building modules to expand E3 capabilities, and using computing platforms (e.g., Jupyter Notebook) to call on E3 for research applications. E3 support was provided for development of a manufacturing capital investment tool (SITExpress) as well as for redevelopment of the BLCC software tool under an interagency agreement with DOE FEMP.
In FY25, E3 support has continued to be provided for both internal and external tool development using the E3 API, as needed, including for SITExpress and BLCC. The underlying energy price projection and LCA data will be updated in [PV]2, and new features will begin to be incorporated to improve the usability and functionality for users.
In FY26, E3 will continue to support these tools. Feature expansion to [PV]2 will continue, including the ability to upload solar installation quote, system specification, and electricity bill documents and automatically extract and populate information into the user interface for easier and faster analysis.
In addition to these activities, this project will assess the value added of potential additional new features for these existing tools and/or additional decision-support tools that are identified as potentially beneficial for stakeholders.
Also, cross-project and cross-program collaborations have been identified, providing synergies across related research activities in EL and NIST, including building and infrastructure related activities in the Measurement Science for Building Systems Program, Circular Economy Program, and Carbon Capture and Accounting Program, with a focus on LCA standards, models, and dataset needs.
In FY25, the project team has developed example LCA model datasets for a range of building products, both construction materials (concrete, asphalt, gypsum board) and building systems (rooftop photovoltaic systems), that have been used to publish detailed public secondary data gap assessments. The models are published through NIST as well as available on the FLCAC in NIST’s group of repositories.
In 2026, LCA models will continue to be developed and released to the public for other construction materials and building systems, including additional products in the current product categories as well as at least one new product category (concrete masonry products). Other products are under consideration, including steel, glass, and multiple building system components.
The project team is also coordinating on LCA secondary dataset standardization efforts through conjunction with the FLCAC working group; participation on ACLCA’s Board and appropriate Committee activities; and coordination with key industry partners (e.g., Product Category Rule Committees) and SDOs (e.g., ASTM) on assessing LCA standards and secondary models and dataset needs.
In additional to these activities, researchers are evaluating opportunities for leveraging machine learning and artificial intelligence to increase interoperability and digitization in the LCA community as well as improve researcher productivity and capabilities in the areas of economic analysis, LCA, and support tools.
In FY25, the project team is using an LLM to automate the extraction and parsing of inconsistent data formats (e.g., non-standardized PDF files) and converting the data into standardized, machine-readable content (e.g., standardized machine-readable files) to allow for transparent, comparable information and associated analysis. The initial application will provide a single step conversion of EPDs (typically available in PDFs) into OpenEPD JSON files. The project team will pilot the tool for several product categories and use the resulting files to compile a public, machine-readable database. An internal web application (ParsEPD) is being developed as a proof of concept.
In FY2026, the project team will develop a publicly available version of ParsEPD. The project team will also apply the same approach to solar installation quotes, photovoltaic specifications, and electricity bill documents to extract information useful in LCCA of rooftop photovoltaics as used in the [PV]2 web application.
The results from implementation of LLMs into the research and web application development workflow will provide greater guidance to the team, EL, and NIST about potential applications of AI in NIST research, dataset development (e.g., conversion and comparison of reported modeling assumptions in product declaration information), and decision-support tool design (e.g., automating uploading user data or chatbot versions of existing tools).
