Large language models for building energy applications: Opportunities and challenges

Building Simulation, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 17, 2025

Language: Английский

---

Potential Role and Challenges of ChatGPT and Similar Generative Artificial Intelligence in Architectural Engineering

SSRN Electronic Journal, Journal Year: 2023, Volume and Issue: unknown

Published: Jan. 1, 2023

The incorporation of generative artificial intelligence (AI) systems, such as ChatGPT, holds great potential in reshaping diverse facets architectural engineering. This research investigates the profound influence AI technologies on structural engineering, HVAC (Heating, Ventilation, and Air Conditioning) electrical plumbing fire protection sustainability, net zero, green building design, information modeling (BIM), urban planning, project management. In ChatGPT's capacity to analyse extensive datasets simulate intricate structures expedites design process, ensuring integrity while optimizing materials costs. it aids devising energy-efficient systems climate control solutions, significantly contributing sustainable practices. Similarly, AI's capabilities enhance optimization both safety reliability. ChatGPT assists creating efficient layouts suppression compliance with regulations. Moreover, plays a pivotal role advancing sustainability design. By evaluating environmental factors suggesting eco-friendly designs, fosters development environmentally responsible structures. domain BIM, facilitates seamless collaboration, automates model generation, improves clash detection, streamlined execution. Nevertheless, integration engineering presents challenges. Ethical concerns, data security, necessity for skilled professionals interpret AI-generated insights are significant issues. delves into these contribution challenges effectively harness AI, paving way transformative era

Language: Английский

---

Automated data mining framework for building energy conservation aided by generative pre-trained transformers (GPT)

Energy and Buildings, Journal Year: 2024, Volume and Issue: 305, P. 113877 - 113877

Published: Jan. 2, 2024

Language: Английский

---

A general energy-aware framework with multi-modal information and multi-task coordination for smart management towards net-zero emissions in energy system

Renewable and Sustainable Energy Reviews, Journal Year: 2025, Volume and Issue: 212, P. 115387 - 115387

Published: Jan. 22, 2025

Language: Английский

---

Automated data-driven building energy load prediction method based on generative pre-trained transformers (GPT)

Energy, Journal Year: 2025, Volume and Issue: unknown, P. 134824 - 134824

Published: Feb. 1, 2025

Language: Английский

---

Integrating ChatGPT, Bard, and leading-edge generative artificial intelligence in architectural design and engineering: applications, framework, and challenges

SSRN Electronic Journal, Journal Year: 2023, Volume and Issue: unknown

Published: Jan. 1, 2023

This research paper delves into the integration of advanced generative artificial intelligence (AI) models, such as ChatGPT, Bard, and similar architectures, within realms architectural design engineering. The comprehensive study explores various aspects, including applications, frameworks, challenges, prospective developments in context In domain design, investigates transformative impact on Architectural Theory, highlighting how AI fosters creativity innovation thinking. Design Process is scrutinized, showcasing models streamline ideation, iteration, collaboration among teams. role Representation Visualization explored, emphasizing its capacity to generate immersive realistic visualizations. Furthermore, examines influence Interior Design, Urban Planning, considers nuanced aspects Cultural Social factors, elucidating these technologies contribute inclusive context-sensitive practices. Within realm engineering, assesses Structural Engineering, demonstrating potential optimize innovate structural analysis designs for enhanced safety efficiency. It applications Building Systems Construction Management, illustrating can project workflows resource allocation. compliance with Codes Regulations analyzed, error reduction adherence standards. Additionally, probes Materials Technology, advancements material selection construction methodologies. also promoting Sustainability Environmental energy efficiency, reduce environmental impact, enhance overall sustainability. While presenting critically evaluates challenges posed by integrating domains, ethical considerations, bias mitigation, user adaptability. Finally, it outlines future directions development, necessity interdisciplinary collaboration, guidelines, ongoing fully harness shaping

Language: Английский

---

Probabilistic machine learning for enhanced chiller sequencing: A risk-based control strategy

Energy and Built Environment, Journal Year: 2024, Volume and Issue: unknown

Published: March 1, 2024

Multiple-chiller systems are widely adopted in large buildings due to their high flexibility and efficiency providing cooling capacity. A reliable robust chiller sequencing control strategy is crucial ensure the energy stability of multiple-chiller systems. However, conventional strategies usually based on real-time measured load without considering changes following hours. Conventional rule-based may result unnecessary switching off, leading waste impairing system stability. Therefore, this study proposes a that utilizes probabilistic predictions. 1h-ahead prediction form normal distribution made using natural gradient boosting (NGBoost). Compared machine learning algorithms, NGBoost can predict not only future but also uncertainty predicted load, which enables handle uncertainties associated with data/measurements adequately. novel risk-based developed The data experiment shows proposed significantly improve reliability plant by reducing total number up 43.6%.

Language: Английский

---

Domain-specific large language models for fault diagnosis of heating, ventilation, and air conditioning systems by labeled-data-supervised fine-tuning

Applied Energy, Journal Year: 2024, Volume and Issue: 377, P. 124378 - 124378

Published: Sept. 5, 2024

Language: Английский

---

Evaluation of large language models (LLMs) on the mastery of knowledge and skills in the heating, ventilation and air conditioning (HVAC) industry

Energy and Built Environment, Journal Year: 2024, Volume and Issue: unknown

Published: March 1, 2024

Large language models (LLMs) have shown human-level capabilities in solving various complex tasks. However, it is still unknown whether state-of-the-art LLMs master sufficient knowledge related to heating, ventilation and air conditioning (HVAC) systems. It will be inspiring if can think learn like professionals the HVAC industry. Hence, this study investigates performance of on mastering skills industry by letting them take ASHRAE Certified Designer examination, an authoritative examination Three key are explored: recall, analysis application. Twelve representative tested such as GPT-3.5, GPT-4 LLaMA. According results, passes with scores from 74 78, which higher than about half human examinees. Besides, GPT-3.5 twice out five times. demonstrates that some great potential assist or replace humans designing operating they make mistakes sometimes due lack knowledge, poor reasoning unsatisfactory equation calculation abilities. Accordingly, four future research directions proposed reveal how utilize improve industry: teaching use design tools software industry, enabling read analyze operational data systems, developing tailored corpuses for assessing real-world operation scenarios.

Language: Английский

---

Integrating ChatGPT, Bard, and leading-edge generative artificial intelligence in building and construction industry: applications, framework, challenges, and future scope

SSRN Electronic Journal, Journal Year: 2023, Volume and Issue: unknown

Published: Jan. 1, 2023

The infusion of generative artificial intelligence (AI), as exemplified by models such ChatGPT and Bard is proving to be a revolutionary catalyst within the building construction sector. This exploration delves into myriad applications, establishes conceptual framework, confronts challenges, delineates prospective trajectory harnessing AI across diverse stages lifecycle. In domain project management scheduling, contribute optimal resource allocation, task sequencing, timeline optimization, thereby elevating overall efficiency delivery. Design optimization equally pivotal, assists architects engineers in crafting innovative designs that concurrently adhere functional aesthetic criteria. predictive prowess fortifies risk management, furnishing stakeholders with insights potential risks effective mitigation strategies. Meanwhile, realm cost estimation budgeting, enhanced accuracy speed offered optimize financial planning allocation. Supply chain benefits from streamlined processes driven insights, ensuring timely cost-effective procurement materials. Generative linchpin quality control, identifying defects deviations standards enhance quality. Real-time data analysis strengthens site monitoring safety protocols, enabling proactive secure working environment. Collaboration communication teams are augmented AI, facilitating seamless information exchange decision-making processes. Predictive maintenance asset undergo transformation, algorithms predicting equipment failures optimizing schedules. Furthermore, integration tackles imperative energy sustainability Models like bard significantly for conservation sustainable practices. paper also explores incorporation reality (AR), virtual (VR), Building Information Modeling (BIM). Ethical concerns, privacy, robust cybersecurity measures necessitate careful consideration. As industry embraces these innovations, substantial improvements efficiency, sustainability, outcomes poised unfold.

Language: Английский

---