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Open research questions in Building Energy and Comfort Optimization

48 unresolved questions extracted from the limitations and future-work sections of 892 Building Energy and Comfort Optimization papers in our library. Each links back to the study that raised it.

What the literature leaves open

  • review. learning, literature that AI 7.1 Conclusion This study examined the role of artificial intelligence (AI) in enhancing passive design strategies for through a climate-responsive affordable housing systematic…

    AI-Assisted Passive Design Strategies for Climate-Responsive Affordable Housing in Nigeria: A Systematic Literature Review and Conceptual Framework · 2026 · DOI

  • Dry-season simulations suggested a possible reversal of performance under near-calm harmattan conditions; however, the magnitude and direction of this effect remain uncertain because of EPW boundary-condition limitations.

    Thermal Mass–Ventilation Interaction in Naturally Ventilated School Classrooms: A Building Performance Simulation Study Evaluated Against Field Measurements in South East Nigeria · 2026 · DOI

  • Research limitations/implications This study is limited to a simulation-based evaluation using Baghdad EPW climate data and static Mashrabiya-inspired louvre configurations.

    Evolutionary optimisation of Mashrabiya-inspired façade shading as an adaptive passive cooling strategy for Baghdad's hot-arid climate · 2026 · DOI

  • While many previous studies rely on fixed discount rates or simplified payback indicators, the present study integrates variable discount rate scenarios and sensitivity analysis to better reflect real-world economic uncertainty, thereby addressing an important methodological gap in the literature. However, as emphasized in both the EPBD framework and recent economic evaluation studies, energy savings alone are insufficient for guiding investment decisions; the economic feasibility of insulation strategies must also be explicitly assessed. Overall, the results emphasize that thermal performance alone is insufficient for guiding insulation material selection in both retrofit and new construction projects.

    Economic Evaluation of Building Insulation Strategies Using Net Present Value and Sensitivity Analysis · 2026 · DOI

  • Future work should focus on improving control strategies, including the consideration of indoor–outdoor temperature differences, as well as the development of computational models and build- ing-scale simulations to evaluate system performance and optimize design parameters under real climatic conditions.

    Concept of an autonomous night cooling system as an alternative to active mechanical cooling · 2026 · DOI

  • While geospatial technologies underpin many UBEM applications, their roles in structuring and advancing UBEM workflows remain insufficiently synthesized.

    The potential of geospatial technologies in urban building energy modeling: a review and future perspectives · 2026 · DOI

  • Risk of overheating and uneven airflow under weak natural driving forces Short-circuiting, local stagnation, and sensitivity to occupant…

    Computational Fluid Dynamics in Hybrid Passive–Active Heat Recovery Systems for High-Performance Buildings: A Critical Review · 2026 · DOI

  • This study introduces accd as a novel comfort-oriented metric that quantifies the thermal gradient between outdoor climatic conditions and adaptive comfort temperature. Different from conventional energy performance indicators, accd provides a scalable and interpretable measure of the climatic effort required to maintain comfortable indoor conditions under variable environmental stressors. By bridging building-level assessments with urban-scale climate dynamics, this metric enables new forms of comfort-based mapping and comparative analysis across cities, addressing a critical gap in current assessment frameworks that abstract buildings from their climatic and urban conoffers a relevant contribution because it text. Methodologically, accd formulates adaptive comfort as a continuous thermal gradient, enabling consistent comparison of climatic and morphological influences across seasons and under different urban scenarios. Beyond the metric itself, a key methodological contribution lies in the quantification of seasonal asymmetry in the determinants of adaptive comfort at urban scale. The framework reveals how the relative influence of morphological versus intrinsic building factors varies between cooling and heating periods, providing evidence of the dual, season-dependent nature of thermal adaptation. This capacity to characterize seasonal transitions in comfort drivers represents a significant advance over single-season or annual-average approaches. However, several limitations must be acknowledged. First, the study relies on EPC data, which is subject to the well-documented performance gap between certified efficiency and actual in-use performance. Second, comfort temperatures were calculated theoretically using the ASHRAE adaptive model, but the entire calculation chain lacks empirical validation against monitored indoor conditions. This introduces potential discrepancies between predicted and actual thermal performance that cannot be quantified within the current framework. Third, temporal resolution is limited. The analysis relies on static seasonal comparisons (winter versus summer) rather than time series data, preventing assessment of within-season dynamics, interannual variability or long-term adaptation trajectories under climate change. Fourth, the spatial scope is constrained to Zone A1 of Zaragoza. The exclusion of other urban contexts such as the historic city center, industrial estates or low-density peripheral developments limits the generalizability of findings. Additional methodological assumptions require acknowledgment. The 300-m buffer radius used to characterize morphological context, while supported by the 3–30–300 rule for green space health benefits, represents a fixed spatial scale that may not capture all morphological influences.

    Assessing seasonal building thermal adaptation through the acclimatization distance: a GIS-based machine learning framework · 2026 · DOI

  • Biometric feedback integration with adaptive lighting systems tested in VR environments has not been validated for real-world implementation; studies comparing user satisfaction, performance outcomes, and physiological responses between biometrically-optimized VR-designed lighting systems and conventional lighting in actual occupancy are absent.

    Evaluating interior lighting as an indoor environmental quality component using virtual reality · 2026 · DOI

  • Implementation pathways for integrating VR-based design reviews into standard architectural design workflows have not been empirically tested; case studies documenting iterative VR lighting evaluation processes in real design projects, cost-benefit analyses, and adoption barriers across different design practice types are lacking.

    Evaluating interior lighting as an indoor environmental quality component using virtual reality · 2026 · DOI

  • The interaction effects between lighting parameters (illuminance levels, correlated color temperature, luminance distribution) and other indoor environmental quality factors (thermal comfort, acoustics) have been identified as an emerging research trajectory, but systematic VR-based experimental designs isolating and measuring these interaction effects remain underdeveloped.

    Evaluating interior lighting as an indoor environmental quality component using virtual reality · 2026 · DOI

  • The calibration accuracy and visual accuracy of photometric rendering in VR systems relative to real-world lighting effects have not been comprehensively validated; systematic studies comparing biometric measurements (EEG, eye-tracking, HRV) and behavioral performance tasks obtained in calibrated VR simulations versus physical environments with identical illuminance, CCT, and glare control parameters are needed.

    Evaluating interior lighting as an indoor environmental quality component using virtual reality · 2026 · DOI

  • Exposure durations in VR lighting studies are characteristically short; longitudinal VR-based assessments measuring long-term effects of dynamic lighting conditions, circadian-responsive systems, and adaptive lighting on cognitive performance, wellbeing, and circadian rhythm entrainment over weeks or months are absent from current literature.

    Evaluating interior lighting as an indoor environmental quality component using virtual reality · 2026 · DOI

  • VR lighting studies rely predominantly on student participant cohorts in controlled laboratory settings; research gaps exist in testing VR-based lighting evaluation protocols with diverse age groups, occupational populations, and individuals with visual impairments across different spatial typologies (offices, healthcare facilities, residential spaces).

    Evaluating interior lighting as an indoor environmental quality component using virtual reality · 2026 · DOI

  • Multi-sensory integration in VR lighting simulations remains underdeveloped; while visual realism in photometric rendering is achieved, thermal feedback, olfactory simulation, and spatial acoustics integration with lighting conditions have not been systematically evaluated for their combined effects on occupant responses.

    Evaluating interior lighting as an indoor environmental quality component using virtual reality · 2026 · DOI

  • Future work should focus on validation using field data and hardware- in-the-loop experimentation to assess performance under operational conditions. Future research may explore adaptive or learning-based envelope definitions that reflect user comfort preferences, energy pricing signals, or long-term system health considerations. While this approach supports transparency and ensures fair comparison across controllers, it does not account for context-dependent preferences or evolving operational objectives.

    From Optimization to Stability Preservation: A Self-Healing, Action-Bearing Digital Twin for Climate-Stressed Building Energy Systems · 2026 · DOI

  • Current neuron selection formulas (e.g., L = √m + n + a) for hidden layers in daylighting ANNs lack theoretical grounding; effective methods that provide principled guidance for selecting the number of neurons based on problem complexity, input dimensionality, and output variables in daylighting control systems need to be developed.

    A Review on Daylighting Prediction by Using Artificial Neural Network Techniques · 2026 · DOI

  • Most ANN daylighting prediction models are trained for specific building geometries and configurations; research on integrating geometric parameters (e.g., window size, overhang depth, room dimensions) into generalizable models that can transfer across new buildings with different geometric constraints remains insufficient.

    A Review on Daylighting Prediction by Using Artificial Neural Network Techniques · 2026 · DOI

  • The trade-off between preventing overfitting through high precision training cycles and avoiding erroneous training data from experiments remains unresolved in ANN daylighting models; optimization of both the number of training cycles and input data quality thresholds requires systematic analysis.

    A Review on Daylighting Prediction by Using Artificial Neural Network Techniques · 2026 · DOI

  • ANN models for daylighting prediction often cannot extrapolate beyond the operating range of training data; methods for systematically selecting training samples that represent the entire operating range of luminance, illuminance, and geometric parameters across different seasons and weather conditions need development.

    A Review on Daylighting Prediction by Using Artificial Neural Network Techniques · 2026 · DOI

  • The standard practice of using three years of training data for ANN daylighting models lacks empirical justification; the optimal time scale for input data remains unstandardized and should be investigated to determine whether shorter or longer periods improve generalization across different climate zones and building types.

    A Review on Daylighting Prediction by Using Artificial Neural Network Techniques · 2026 · DOI

  • Almost all ANN models for daylighting prediction use the basic backpropagation (BP) algorithm for training, but advanced optimization variants such as Levenberg-Marquardt (LM), conjugate gradient methods, momentum-based approaches, and adaptive learning rate techniques have not been systematically explored or compared for daylighting prediction tasks.

    A Review on Daylighting Prediction by Using Artificial Neural Network Techniques · 2026 · DOI

  • The main problems are the following: the actual technical condition of these buildings is unknown (technical studies are needed), there are no freely available management fee savings for residents to pay for fundamental studies and repairs or renovations, there is insufficient or difficult access to public support for improving energy efficiency and the overall technical condition of buildings.

    Technical Condition of Soviet-Era Apartment Buildings, Related Problems and Possible Solutions in Latvia · 2023 · DOI

  • As uncertainties related to nZEB performance level and cost calculation are generally much higher due to high performance technical solutions not commonly used and costs not well established, it is recommended to repeat nZEB calculations with possibly refined input data before setting mandatory nZEB requirements.

    Cost optimal and nearly zero energy performance requirements for buildings in Estonia; pp. 183–202 · 2013 · DOI

  • , heat waves and cold snaps) on retrofitted buildings was not investigated. Therefore, further efforts are warranted to develop a user-friendly platform that enhances the framework’s accessibility.

    Occupant-centric energy retrofit evaluation and optimization for Canadian residential buildings: a life cycle thinking approach · 2026 · DOI

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48 open questions have been extracted from the limitations and future-work passages of 892 Building Energy and Comfort Optimization papers in our library. Each one below links back to the study that raised it, so you can read the original claim in context.

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