Power Loss Research Articles

Experimental and Simulated Investigation of S-parameters and Power Loss Characteristics of PTFE/Glass Composites at X-band Frequency

Polytetrafluoroethylene (PTFE)-based substrates are in high demand for high-frequency (microwave) applications because of their low relative permittivity, enabling efficient signal transfer. In this work, PTFE composites have been prepared with different content (5 wt.% - 25 wt.%) of soda lime silica glass (SLSG) for substrate application. The composites were characterized by their complex permittivity and S-parameters through the rectangular waveguide (RWG) measurement method over x-band frequency (8.2 GHz – 12.4 GHz). The RWG set-up was connected to a vector network analyser for the characterization. Power loss of the composites due to material absorption was calculated using the measured S-parameters. As the content of the SLSG increased from 5 - 25 wt.%, complex permittivity rose from 2.18-j0.0035 to 2.56-j0.0047 in the frequency range considered. In addition, |S11| reduced from 0.623 and 0.700 to 0.418 and 0.441, whereas |S21| varied from 0.780 and 0.713 to 0.906 and 0.895 for 5 wt.% and 25 wt.% SLSG contents at 8.2 GHz and 12.4 GHz, respectively. The calculated power loss increased from 2.94 dB to 3.29 dB and 4.01 dB to 4.88 dB for the same filler contents and frequency. Furthermore, the S-parameters were simulated using the finite element method (FEM) via COMSOL software and compared with the measured values. The comparison revealed a mean relative error of < 0.1, denoting the accuracy of the RWG method. Also, the electric field distribution across the waveguide length was visualized. Thus, the optimal performance of the composite was found at 5 wt.% SLSG filler content for microwave substrate application.

Optimizing energy-efficient grid performance: integrating electric vehicles, DSTATCOM, and renewable sources using the Hippopotamus Optimization Algorithm

The rapid increase in renewable energy integration and electric vehicle (EV) adoption creates significant challenges for the stability and efficiency of power distribution networks. This study addresses the need for optimized placement and sizing of Electric Vehicle Charging Stations (EVCSs), photovoltaic (PV) systems, and Distribution Static Compensators (DSTATCOMs) to enhance grid performance. The motivation for this work arises from the fluctuating nature of renewable energy generation and the unpredictable demands of EV charging, which strain existing infrastructure. To address these challenges, we propose a novel optimization framework that introduces the Renewable Distributed Generation Hosting Factor (RDG-HF) and Electric Vehicle Hosting Factor (EV-HF) as key metrics. These metrics, combined with the Hippopotamus Optimization Algorithm (HO), enable strategic planning within the IEEE 69-bus system. Simulation results demonstrate that the integrated placement of EVCSs, PVs, and DSTATCOMs reduces power losses by up to 31.5% and reactive power losses by up to 29.2%. An economic analysis further reveals payback periods ranging from 2.7 to 10.4 years and potential profits of up to $1,052,365 over 25 years. These findings highlight the importance of optimized integration in improving both technical performance and long-term economic benefits for distribution networks.

Z source based switched capacitor nine level boost inverter with a modified modulation strategy

This article presents a Z source (ZS) based switched capacitor multilevel inverter (SC-MLI) with low capacitors charging inrush currents utilizing a modified modulation strategy. The topology generates nine output voltage levels with quadruple voltage gain utilizing eight power switches, five capacitors, two inductors, four discrete diodes, and a single DC source. The voltage gain can be further increased by applying shoot through (ST) states to the frontend ZS-network. Owing to its high voltage gain, the topology is suitable for low voltage renewable energy sources such as photovoltaics (PV), and fuel cells (FC). A modified modulation strategy is presented based on the conventional level shifted sinusoidal pulse width modulation (LS-SPWM). The proposed modulation strategy improves the dc-link utilization at higher modulation index. A detailed mathematical analysis is provided for the gain calculation based on the modified modulation strategy. A comparative study is implemented to verify the merits of the proposed topology. A simulation model is implemented utilizing MATLAB / Simulink to verify the topology characteristics. The power losses and efficiency calculations are presented using Altair PSIM. Furthermore, an experimental prototype is constructed to verify the simulation findings. The topology is tested with different loading conditions at numerous modulation index values and ST duty ratios. Furthermore, step change conditions are implemented to test the topology response. The effect of the ZS network on the switched capacitors charging inrush currents is validated. The proposed topology shows an overall advantage in terms of the output characteristics as well as the hardware requirements.

Improvement of the magnetization and heating ability of CoFe2O4/NiFe2O4 core/shell nanostructures

Abstract In this study, the effect of the shell thickness on the structural and magnetic properties of the CoFe2O4/NiFe2O4 core/shell is studied. A single-phase core/shell nanocomposite was prepared by the hydrothermal method. The shell thickness was found to control the magnitudes of saturation magnetization and coercive field of the prepared samples. The thickness of the NiFe2O4, which covered cubic CoFe2O4 particles of 15 nm, was 1.8 nm, leading to an increase in the saturation magnetization by 26% and a decrease in the coercive field by 50% compared to bare CoFe2O4. However, a further increase in shell thickness caused interfacial dislocations due to the lattice mismatch between the core and the shell. Finally, the heating ability at high frequency was measured for all samples. Comparing the temperature rise under the influence of AC magnetic field, which indicates power loss, relative to bare CoFe2O4, it was enhanced by 100% for a shell thickness of 26 nm. The results of this study point to potential applications for these samples in the field of magnetic hyperthermia for cancer therapy and drug delivery.

Optimal operation of the smart electrical network considering energy management of demand side

The smart electrical grid represents a significant advancement in generating, distributing, and consuming electricity. This sophisticated system integrates modern technology and communication tools to enhance energy management efficiency and improve demand costuming within the power network. In this paper, optimal operation of the electrical network with energy management and demand response program (DRP) is implemented. The implementation of the optimal operation is done via multi-stage and multi-objective functions modeling. The DRP modeling is done in first stage to optimal management of consumption in demand side. In second stage, operating cost, emission, power losses and voltage profile are optimized as multi-objective functions modeling with attention to optimal management of consumption in demand side. The solving optimal operation of the electrical network is carried out by using elephant herding optimization (EHO). This problem is implemented on 33-bus test system with hybrid energy resources. Finally, DRP leads to reducing costs, emissions and losses and improving voltage profile in proposed electrical network. Hence, operation costs, emission, power losses, and voltage deviation with the participation of DRP are minimized by 39.15%, 9.94%, 33.35%, and 30.73%, respectively. On the other side, voltage stability is enhanced by 3.66% without considering DRP.

THE IMPACT OF ELECTRIC POWER OUTAGE ON THE PROFITABILITY OF SMALL BUSINESSES IN NIGERIA: A CASE STUDY OF GWAGWALADA TOWN

This study examined the impact of electric power outages on the profitability of small businesses in Nigeria, using 50 randomly selected small businesses in Gwagwalada town as a case study. A Logit regression model was adopted, incorporating a mix of qualitative and quantitative variables. The Maximum Likelihood (ML) estimation method was utilized in estimating the Logit model. Findings from the estimated Logit model showed that electric power outages had a negative impact on the profitability of small businesses in Gwagwalada town, while small businesses' expenses on alternative electricity power supplies had a positive impact on profitability. However, both electric power outages and small businesses’ expenses on alternative electricity power supplies in Gwagwalada town had an insignificant impact on the profitability of the small businesses. Based on the findings of the study, it was recommended, among other things, that the government should undertake a national demand study to determine the exact electricity requirements to meet demand in the short, medium, and long terms. Furthermore, an integrated least-cost system expansion plan should be developed for the efficient deployment of the Nigerian electricity industry in the medium and long terms. There is also a need for diversification of electricity generation to improve the security of supply, as well as the development of capacity to generate electricity closer to demand centers to reduce technical losses. Additionally, the government should explore and develop measures to ensure the long-term supply of gas for electricity generation.

Transient and Steady-State Evaluation of Distributed Generation in Medium-Voltage Distribution Networks

As power generation systems with increasingly higher capacities are interconnected with distribution networks, a pressing need arises for a thorough analysis of their integration and the subsequent impacts on medium-voltage lines. This study conducts a comprehensive evaluation, encompassing both steady-state and transient behaviours, leading to a holistic assessment of a real-world biogas generation system integrated into a medium-voltage network. Although the methodology does not introduce revolutionary concepts, its detailed application on a real feeder under various operating conditions adds practical value to the existing body of knowledge. The methodology explores various aspects, including voltage profiles, load capacity, power losses, short-circuit currents, and protection coordination in steady-state conditions. Additionally, a transient analysis is performed to examine the system’s response under fault conditions. This systematic approach provides a deep understanding of the system’s behaviour across diverse operational scenarios, enriching the field with practical insights. The key contributions of this study include identifying the effects of distributed generation systems (DGSs) on short-circuit currents, protection coordination, and defining voltage levels that briefly exceed the CBEMA quality curve. The benefits of incorporating a generation system into a distribution network are discussed from various technical perspectives. In a peak demand scenario, with a 1.72 MW generation capacity, the phase current experiences a notable reduction of 35.78%. Concurrently, the minimum peak demand voltage increases from 12.62 to 12.83 kV compared to a nominal voltage of 12.7 kV. Furthermore, the contribution of the generation system to the short-circuit current remains minimal, staying below 4% even under the most adverse conditions. However, our findings reveal that voltage levels exceed the upper limit of the CBEMA quality curve briefly during a single-phase fault with generation, which could potentially damage electronic equipment connected to the grid. Nonetheless, the likelihood of encountering a single-phase grounding fault with zero resistance remains low.

Optimizing Microgrid Performance: Integrating Unscented Transformation and Enhanced Cheetah Optimization for Renewable Energy Management

The increased integration of renewable energy sources (RESs), such as photovoltaic and wind turbine systems, in microgrids poses significant challenges due to fluctuating weather conditions and load demands. To address these challenges, this study introduces an innovative approach that combines Unscented Transformation (UT) with the Enhanced Cheetah Optimization Algorithm (ECOA) for optimal microgrid management. UT, a robust statistical technique, models nonlinear uncertainties effectively by leveraging sigma points, facilitating accurate decision-making despite variable renewable generation and load conditions. The ECOA, inspired by the adaptive hunting behaviors of cheetahs, is enhanced with stochastic leaps, adaptive chase mechanisms, and cooperative strategies to prevent premature convergence, enabling improved exploration and optimization for unbalanced three-phase distribution networks. This integrated UT-ECOA approach enables simultaneous optimization of continuous and discrete decision variables in the microgrid, efficiently handling uncertainty within RESs and load demands. Results demonstrate that the proposed model significantly improves microgrid performance, achieving a 10% reduction in voltage deviation, a 10.63% decrease in power losses, and an 83.32% reduction in operational costs, especially when demand response (DR) is implemented. These findings validate the model’s efficacy in enhancing microgrid reliability and efficiency, positioning it as a viable solution for optimized performance under uncertain renewable inputs.

Fault Prediction and Reconfiguration Optimization in Smart Grids: AI-Driven Approach

Smart grids (SGs) are essential for the efficient and distributed management of electrical distribution networks. A key task in SG management is fault detection and subsequently, network reconfiguration to minimize power losses and balance loads. This process should minimize power losses while optimizing distribution by balancing loads across the grid. However, the current literature yields a lack of methods for efficient fault prediction and fast reconfiguration. To achieve this goal, this paper builds on DEN2DE, an adaptable routing and reconfiguration solution potentially applicable to SGs, and investigates its potential extension with AI-based fault prediction using real-world datasets and randomly generated topologies based on the IEEE 123 Node Test Feeder. The study applies models based on Machine Learning (ML) and Deep Learning (DL) techniques, specifically evaluating Random Forest (RF) and Support Vector Machine (SVM) as ML methods, and Artificial Neural Network (ANN) as a DL method, evaluating each for accuracy, precision, and recall. Results indicate that the RF model with Recursive Feature Elimination (RFECV) achieves 94.28% precision and 81.05% recall, surpassing SVM (precision 89.32%, recall 6.95%) and ANN (precision 72.17%, recall 13.49%) in fault detection accuracy and reliability.

Start Over After Pre‐Empt (SOAP) Protocol

ABSTRACTConsider a job that normally requires units of time to complete. A higher authority comes and interrupts the service. The inter‐arrival times of the interrupts are , which are the actual available service times to work on the job. Thus, if the first available service time is larger than , the job gets completed, and the remaining service time is the first available service time for the next job. If not, the previous service is lost and service on the job starts from scratch using the next available service time. As before, if , the job gets completed and the remaining service time is the first available service time for the next job. If not, the service is lost, and is the available service time for the job. And so on. Let be the time to complete the job. This is called the start over after pre‐empt (SOAP) protocol. An example of such interrupts is power outages. After a power outage interrupt the partial service on a job running on a computer is lost and service on the job has to start again. We study properties of and , the time to complete two jobs normally requiring times , and give some guidance whether when . We obtain the asymptotic distribution of a stochastic process based on which has interesting independent increments of a new type. My frustrations standing in a queue in India, where a supervisor interrupts and the service on my job has to start again, were my inspiration for the protocol named here as SOAP. A careful referee pointed out that the SOAP protocol is not new in the queues literature. It goes by the name RESTART and has variants called RESUME and REPLACE.

Effective Market Power and Welfare Loss

ABSTRACTThis paper introduces a straightforward and effective estimation methodology for quantifying firm‐level welfare losses attributable to market power in monopolistic competition markets. Our analysis underscores that welfare losses are primarily contingent on effective market power, expressed as the product of the Lerner index and market share. Furthermore, our study demonstrates that welfare loss computed using the Hicksian measurement is smaller than that obtained through the Marshallian measurement. Finally, we apply this methodology to estimate firm‐level market power and welfare losses in the Chinese carbonated beverage industry.

Ukraine's Strategy to Counter Russian Cyber Threats in the Russo–Ukrainian War

This study investigates the cyber threats that Russia poses to Ukraine and examines the strategies that Ukraine employs in response. The Russian cyber operations are believed to have started covertly before the beginning of the Russia-Ukraine War in 2022. These operations peaked when Russia targeted the Kyiv Post news agency and the KA-SAT satellite, resulting in significant communication disruptions and power outages within Ukraine, which affected both the government and society. The research utilizes theories of security strategy, cyber threats, and cybersecurity strategy to analyze the cyber tactics used during the Russia-Ukraine conflict. Employing qualitative methods and case study models, the study describes Russia's cyber operations that threaten Ukraine’s security, as well as Ukraine's responses to these threats. The operations included information manipulation and attacks on critical infrastructure. Findings reveal that the Ukrainian government implemented several effective strategies, such as establishing legal frameworks, creating cybersecurity agencies, and collaborating with the United States. These measures have proven successful in countering Russian cyber-attacks. Through its partnership with the U.S., Ukraine’s rapid response team (CERT) was able to recover systems that had been targeted, thereby enhancing Ukraine’s cyber resilience against Russian threats.

Advanced Distribution System Optimization: Utilizing Flexible Power Buses and Network Reconfiguration

The increasing integration of distributed generation (DG) and the rise of microgrids have reshaped the operation of distribution systems, introducing both challenges and opportunities for optimization. This study presents a methodology that combines network reconfiguration with the integration of buses with flexible power in order to improve the efficiency and cost-effectiveness of distribution networks. Flexible buses, which aggregate multiple microgrids or controllable distributed resources, function as control points that can dynamically adjust active and reactive power within predefined limits. This capability allows for more precise management of power flows, enabling the system to respond to fluctuations in generation and demand. The proposed optimization framework aims to minimize the total operational costs, including power losses and the use of flexible power, while adhering to system constraints. The methodology is evaluated through case studies on two distribution systems: the Kumamoto and IEEE-33 systems. The results indicate a 43.9% reduction in power losses for the Kumamoto system and a 66.6% reduction for the IEEE-33 system, along with notable cost savings in both cases. These outcomes demonstrate the potential benefits of incorporating flexible power buses in modern radial distribution networks, showing their role in adapting to various operational scenarios and supporting the integration of distributed generation and microgrids.

Implementation of Single-Phase Shift (SPS) and Extended Phase Shift (EPS) for Dual Active Bridge (DAB)

Objectives: To improve power transfer and efficiency in Dual Active Bridge (DAB) converters, this study compares and assesses the Single-Phase Shift (SPS) and Extended Phase Shift (EPS) control techniques. Methods: Using the Dual Active Bridge (DAB) arrangement, the research focuses on implementing SPS and EPS control methods to an Isolated Bidirectional Full-Bridge DC-DC Converter (IBDC). A comprehensive review of the IBDC's operating modes and the EPS's control concept is included in this study. Findings: In comparison with EPS, SPS control is limited by a smaller operating range, higher power loss, and higher circulating current. Conversely, EPS exhibits benefits such as decreased back power flow, increased Zero Voltage Switching (ZVS) range, and decreased current stress. These conclusions are supported by the simulation results, which show that EPS control outperforms SPS in terms of operational stability, harmonics, and efficiency. Under the SPS control at different phase shift minimums, THD is 15.06%; whereas, for EPS it is 12.90%. Novelty: This study demonstrates how EPS outperforms SPS in DAB converters, providing better operational range, THD, and efficiency. Keywords: Isolated Bidirectional Full-Bridge DC–DC Converters (IBDCs), Dual Active bridge (DAB), Single Phase Shift (SPS), Extended Phase Shift (EPS), Current Stress, Power Transmission

Challenges and outcomes of airway surgery in a post-war low-resource setting: A case series from Mekelle, Ethiopia.

This study aims to document and analyze the challenges and outcomes of performing complex airway surgery in a low-resource, post-war setting in Mekelle, Ethiopia. This prospective case series examines clinical data from five patients who underwent airway reconstruction surgeries and one patient who underwent total laryngectomy at Ayder Comprehensive Specialized Hospital in Mekelle. Data included patient demographics, airway stenosis etiology and severity, operative details, postoperative outcomes, complications, and hospital length of stay. Ethical approval was obtained from institutional review boards at Mayo Clinic and Mekelle University. The study included six patients aged 9-62 years, with surgeries comprising three cricotracheal resections, two tracheal resections, and one laryngectomy. Three reconstructions were for war-related injuries. Challenges included power outages during surgeries, limitations in medical supplies and equipment, and inadequate perioperative care. Despite these, three patients requiring tracheostomies were successfully decannulated within a year. However, complications such as restenosis, infections, and the need for reintubation were common. Airway surgeries in a low-resource, post-war setting face significant hurdles, including perioperative care quality, resource limitations, and infrastructure issues. Successful outcomes require multidisciplinary training tailored to local contexts, investments in hospital infrastructure and reliable electricity, and proper perioperative nutrition. This study highlights the need for comprehensive interventions to improve surgical care in such settings. Level of evidence: IV.

A Novel Arithmetic Optimization Technique for Electric Vehicle Charging

With the increased usage of Electric vehicles in recent days, the optimal usage of battery both in terms of electrical and economic perspective is very important. Though several battery optimization techniques are evolving day by day, the method to achieve an efficient control of all parameters like battery current, power and power loss has not yet been achieved. This paper proposes a novel approach of implementing an arithmetic optimization scheme for FTP 75 drive cycle source. In this connect, the details of the arithmetic operators are discussed and their relations with electrical parameters are framed from the fundamental equations. A Pseudo-code has been developed and implemented for identifying the optimum charging point from different search spaces. The simulation results obtained for different electrical parameters with respect to different arithmetic operators, emphasizes the enhanced operation of electric vehicles at optimum charging points.

Optimal Integration for DGs with EVs planning in Distribution Networks with Hybrid MC-GA Technique using Realistic Load Models

With the growing integration of Distributed Generations (DGs) and Electric Vehicles (EVs) into distribution grids, the need for efficient and intelligent management strategies has become paramount. The need for power consumption is increasing every day in accordance with the standard demand pattern. As a result, either creating a lot of electricity or minimizing losses is crucial. In order to minimize real and reactive power losses from the system's point of view, this paper presents the optimal performance index-based size and location determination of DGs, EVs and their coordination in distribution networks using realistic load models (RLMs) such as RLM-1, RLM-2, RLM-3, RLM-4, and RLM-5, respectively. Improvement of the system power factor (SPF) is defined in this analysis as the power system's performance both with and without different kinds of DGs and DGs with EVs for various RLMs. PHEVs type of EVs used in this paper. The hybrid Monte Carlo-Genetic Algorithm (MC-GA) is the basis of the simulation technique that is being suggested. Networks with IEEE-16 and 37 buses in their distribution systems have been used to test the suggested methods. Comprehensive simulations on a test distribution network are used to show that the suggested method is effective. The system's performance can be optimized in terms of grid stability, efficiency, and reliability, according to the results. By stressing the significance of employing a hybrid MC-GA technique to meet realistic load circumstances, this research advances optimal DG and EV solutions.

Cumulative effects of H+ and Pi on force and power of skeletal muscle fibres from young and older adults.

The cellular causes of the age-related loss in power output and increased fatigability are unresolved. We previously observed that the depressive effects of hydrogen (H+) (pH 6.2) and inorganic phosphate (Pi) (30mm) did not differ in muscle fibres from young and older men. However, the effects may have been saturated in the severe fatigue-mimicking condition, potentially masking age differences in the sensitivity of the cross-bridge to these metabolites. Thus, we compared the contractile mechanics of muscle fibres from the vastus lateralis of 13 young (20-32years, seven women) and 12 older adults (70-90years, six women) in conditions mimicking quiescent muscle and a range of elevated H+ (pH 6.8-6.6-6.2) and Pi (12-20-30mm). The older adult knee extensor muscles showed hallmark signs of ageing, including 19% lower thigh lean mass, 60% lower power and a greater fatigability compared to young adult muscles. Progressively increasing concentrations of H+ and Pi in the chemically-permeabilized fibre experiments caused a linear decrease in fibre force, velocity and power; however, the effects did not differ with age or sex. Fast fibre cross-sectional area was 41% smaller in older compared to young adults, which corresponded with lower absolute power. Size-specific power was greater in fibres from older compared to young adults, indicating the age-related decline in absolute power was explained by differences in fibre size. These data suggest the age-related loss in power is determined primarily by fast fibre atrophy in men and women, but the age-related increase in fatigability cannot be explained by an increased sensitivity of the cross-bridge to H+ and Pi. KEY POINTS: The causes of the age-related loss in muscle power output and the increase in fatigability during dynamic exercise remain elusive. We show that progressively increasing concentrations of hydrogen (H+) and inorganic phosphate (Pi) causes a linear decrease in muscle fibre force, velocity and power, but the depressive effects of these metabolites on cross-bridge function did not differ in fibres from older compared to young adults across a range of fatigue-mimicking conditions. We also found peak absolute power did not differ in slow fibres from young and older adults but it was ∼33% lower in older adult fast fibres, which was explained entirely by age differences in fibre size. These data suggest that fast fibre atrophy is a major factor contributing to the loss in power of older men and women, but that the age-related increase in fatigability cannot be explained by an increased sensitivity of the cross-bridge to H+ and Pi.

An MPPT method using phasor particle swarm optimization for PV‐based generation system under varying irradiance conditions

AbstractThe dependency of photovoltaic (PV) systems‐based generation systems on constantly varying temperatures and incident sunlight affect the non‐linear behaviour of PV panels. Therefore, tracking the maximum power output of the PV panels for efficient utilization becomes a challenge, resulting in power losses and the creation of intense heating spots in the shaded areas of the PV modules when the PV modules receive varying degrees of insolation, that is, under partial shading conditions (PSCs). The inclusion of bypass diodes in parallel to each PV module mitigates this problem to an extent but leads to the formation of several peaks in the P‐V characteristics. As a result, maximum power point tracking (MPPT) to deliver maximum power at the load becomes a limitation for conventional optimization algorithms as they are normally based on hill climbing algorithm and get stuck at local maxima of the P‐V curve. Therefore, metaheuristic algorithms are used thereby eliminating the possibility of getting trapped at the local optima. However, particle swarm optimization (PSO) suffers from delayed convergence, more iterations to reach the optimal point, and random parameter selection. Hence, this study employs an improved version of PSO called Phasor‐PSO (P‐PSO) in an MPPT controller. The proposed algorithm is parameter‐less which results in reduced computational complexity and thus provides quick decision in achieving the maximum power point (MPP). The hardware‐in‐loop real‐time analysis demonstrates the supremacy of P‐PSO over PSO in faster convergence, higher efficiency, and reduced power losses during tracking under various PSCs. The P‐PSO based MPPT method will find application in grid connected and stand‐alone solar PV system with better efficiency of power transfer.

Assessing the Moisture Resilience of Wood Frame Wall Assemblies

Resilience has been used as a building performance metric that measures the building’s capability of absorption, response, and recovery from one or a series of disruptive events, e.g., extreme weather events or power outage events. With respect to resilience, in relation to the moisture performance of the building envelope (moisture resilience), this aspect has not yet been thoroughly explored nor defined. Given the expected increase in annual precipitation in certain regions of Canada as induced by climate change effects occurring both currently and in the future, the moisture resilience of building envelops will require immediate attention given that wall assemblies of buildings are predicted to be subjected to excessive moisture loads in the coming years. In this study, the moisture resilience of wood frame wall assemblies to mould growth was described from three aspects: (i) absorption—the ability of the wall to maintain a low level of relative humidity on the OSB; (ii) response—the fluctuation of the relative humidity on the OSB; and (iii) recovery—the rate at which the relative humidity recovers to an acceptable level. The metrics used to demonstrate the relative impact of these factors on moisture performance were also developed. The results have revealed a robust correlation between moisture performance and the relative influence of various newly defined aspects of moisture resilience.