Search Results (1,270)

Building Information Modeling (BIM) supports information integration and coordination across the construction lifecycle, but benefits depend on collaboration that is shaped by the selected project delivery method (PDM). BIM-PDM evidence is difficult to consolidate due to heterogeneous terminology and fragmented, context-specific studies. This scoping review maps which PDMs are addressed in the BIM-related literature and how adequacy is framed. Following PRISMA-ScR, Web of Science and Scopus were searched and 71 studies met the eligibility criteria. Publications increased markedly after 2018 and were geographically concentrated, with the largest shares associated with author affiliations in China, the United Kingdom, Australia, Canada, Malaysia, and the United States. Integrated Project Delivery (IPD) was the most frequently examined (46 studies), followed by Design–Bid–Build (DBB) (29), Design–Build (DB) (29), Public–Private Partnership (PPP) (17), and Engineering, Procurement, and Construction (EPC) (14), while Alliancing, Lean-oriented delivery approaches, and Construction Management were comparatively underrepresented. A temporal analysis indicates a recent shift toward collaborative delivery methods in BIM research. Case-based studies are predominantly situated in public sector projects, with DBB, DB, EPC, and IPD examined across both infrastructure and building contexts, while PPP is limited to infrastructure. The literature is largely focused on design and construction phases, with limited attention to early project stages and operation and maintenance. Results indicate both traditional and relationship-based PDMs are studied in the existing literature, with research framing PDMs that allow for early contractor involvement as most compatible with BIM. Moreover, IPD, DB, and EPC show the best alignment compared to most used traditional DBB methods primarily due to the early involvement of the contractor in the project. EPC and DB achieve this through the allocation of responsibility to the contractor, whereas IPD relies on the early engagement of key participants and the systematic alignment of their objectives. Collaborative and relationship-based approaches are consistently presented as the most suitable for BIM, while DBB tends to constrain BIM benefits because of its fragmented nature. This study contributes by providing a systematic synthesis of BIM-PDM relationships in the scientific literature, identifying the key mechanisms underlying the suitability of different delivery methods for BIM implementation, and offering recommendations for future research based on the identified gaps. Full article

The accelerated low-carbon transition of power systems and the widespread integration of Electric Vehicles (EVs) present both severe operational challenges and substantial flexible regulation potential for Active Distribution Networks (ADNs). This paper provides an integrative review of the coordinated control and multi-market bidding mechanisms for EV-centric Technical Virtual Power Plants (TVPPs). Moving beyond descriptive surveys, this review systematically synthesizes the fragmented literature across three critical dimensions: (1) the physical-economic bidirectional mapping, which considers nonlinear power flow constraints and node voltage limits within the TVPP framework; (2) multi-market coupling mechanisms, evolving from unilateral energy bidding to coordinated participation in carbon trading and ancillary services; and (3) real-time control strategies, critically evaluating the trade-offs between optimization techniques (e.g., Model Predictive Control) and cutting-edge artificial intelligence approaches (e.g., Deep Reinforcement Learning) in mitigating battery degradation. Furthermore, a transparent review methodology is adopted to ensure literature rigor. By explicitly outlining the boundaries between TVPPs, Commercial VPPs (CVPPs), and EV aggregators, this paper identifies core unresolved trade-offs among aggregation fidelity, market complexity, and communication latency, providing evidence-backed pathways for future engineering demonstrations and V2G applications. Full article

Building users are key participants in demand response (DR) markets, providing significant flexible resources. Due to uncertainty in market clearing prices, various risk-based decision models have been developed to describe their bidding behavior, typically assuming constant risk preferences. However, empirical evidence indicates that users’ risk attitudes vary with the magnitude of load adjustments. To capture this feature, this paper introduces mental accounting theory to model the risk-aware bidding behavior of building users. Total response capacity is divided into three independent mental accounts based on air-conditioning setpoint adjustment magnitude, representing risk-averse, risk-neutral, and risk-seeking behaviors. This framework allows multiple risk preferences to be represented within a unified bidding model. For each account, response quantity and cost models are developed. Bidding strategies under uncertain market clearing prices are formulated by incorporating loss aversion. A multi-agent simulation framework, including building users, a load aggregator, and a grid operator, is established to simulate the market clearing process. A simulation study is conducted using 19 building clusters located in Zhuhai, China. The proposed model is compared with a single-bid model and a step-wise bidding model with constant risk preferences. The results show that it better captures building users’ multiple risk preferences under market clearing price uncertainty. Users tend to secure stable returns through responses with minimal comfort loss, while pursuing excess profits via higher bids for responses involving greater comfort sacrifices. Full article

To address the challenges posed by multiple uncertainties in modern power systems to the market bidding of Virtual Power Plants (VPPs), this paper proposes an adaptive bidding strategy based on Deep Reinforcement Learning (DRL). First, a heterogeneous VPP aggregation model integrating dedicated energy storage, Vehicle-to-Grid (V2G), and flexible loads is constructed, incorporating complex physical and operational constraints. Second, to overcome the “myopic” local optimality problem of traditional DRL in temporal arbitrage tasks, a potential-based reward shaping mechanism linked to future price trends is designed to guide the agent toward long-term optimal strategies. Finally, multi-dimensional comparative experiments and mechanism analyses are conducted in a simulated day-ahead electricity market. Simulation results demonstrate the following: (1) The proposed algorithm exhibits robust convergence stability and effectively handles stochastic noise in market prices and renewable generation. (2) Economically, the strategy significantly outperforms the rule-based strategy and remains highly competitive with the deterministic-optimization benchmark under perfect-information assumptions. (3) Mechanism analysis further reveals that the DRL agent breaks through the rigid logic of fixed thresholds, learning a non-linear dynamic game mechanism based on “Price-SOC” states, thereby achieving full-depth utilization of energy storage resources. This work provides an interpretable data-driven paradigm for intelligent VPP decision-making in uncertain environments. Full article

This paper reviews recent work on dynamic virtual power plants (DVPPs) using an Energy–Information–Market framework. It addresses the important problem of how DVPPs can support low-inertia power system operation and feeder-level stability under high renewable penetration. First, system-level studies on low-inertia operation and frequency control are used to frame quantitative requirements on rate of change of frequency, nadir, and quasi-steady-state limits. Second, energy-layer models are surveyed, including participation-factor-based DVPP controllers, grid-forming architectures, model-free frequency regulation, and robust frequency-constrained scheduling for allocating virtual inertia and fast frequency response (FFR) across distributed energy resource fleets. Third, information-layer and market-layer models are reviewed, covering stochastic and robust bidding, distribution locational marginal price-based clearing, peer-to-peer and community markets, privacy-preserving coordination, and emerging governance and cybersecurity schemes for DVPP participation. Across these strands, much of the literature remains centred on steady-state active and reactive power dispatch, with dynamic security enforced as constraints rather than formulated as verifiable and tradable services. This review identifies gaps in dynamic metrics and benchmarks, forecasting of available inertia and FFR capacity, market-physics co-design, multi-aggregator interaction, and experimentally validated DVPP implementations. These findings suggest that DVPPs can “sell stability” at the feeder level only through co-designed control, information, and market mechanisms and outline a research roadmap for this purpose. Full article

Strategic bidding for wind–battery hybrid systems is increasingly critical as electricity spot markets transition toward market-oriented mechanisms, particularly in Chinese pilot regions. However, dual uncertainties—wind generation variability and volatile locational marginal prices (LMPs)—expose market participants to significant financial tail risk. This study develops a risk-constrained reinforcement learning framework for optimal bidding of wind–storage hybrid systems. We employ soft actor–critic (SAC) for continuous action control and integrate conditional value-at-risk (CVaR) into reward design to explicitly penalize low-probability, high-loss outcomes. The framework incorporates realistic operational constraints, including linearized battery degradation costs and a market-compatible single-bid abstraction for hourly settlement. Using one-year historical operational data from a 150 MW wind farm (with a 91-day test period), we find that storage integration increases annual profit by 108.4–114.2% relative to wind-only operation. Critically, the SAC–CVaR policy (η = 0.35) preserves 97.3% of risk-neutral profit ($7.71 M vs. $7.93 M) while substantially mitigating downside risk: CVaR@95% improves by 42.4% (−$549 vs. −$952) and VaR@95% improves by 30.1% (−$275 vs. −$393). The trained policy achieves sub-millisecond inference (0.262 ms per decision, ~3820 decisions/s), corresponding to a 3.8 × 10⁴–5.7 × 10⁴× speedup over optimization-based solvers (10–15 s per decision), enabling real-time deployment. Behavioral analysis reveals that the agent learns adaptive, forecast-normalized bidding strategies with more conservative reporting in high-price regimes and counter-cyclical battery dispatch patterns, demonstrating effective coordination between profitability and risk control under volatile market conditions. Full article

The ramping requirement in new power systems primarily stems from net load variations and forecast errors of renewable energy and load. Designing an equitable cost allocation mechanism for ramping services based on these factors facilitates incentives for generation and load to actively reduce ramping demands, thereby alleviating system ramping pressure. Accordingly, this paper proposes a fair ramping cost allocation mechanism based on the ramping responsibility coefficients of market participants. Under this mechanism, a market-oriented operation model for wind–hydro-storage joint operation is established to verify its effectiveness in market applications. First, a ramping cost allocation mechanism is constructed based on ramping responsibility coefficients. According to the responsibility coefficients of market participants for deterministic and uncertain ramping requirements, ramping costs are allocated to the corresponding contributors in proportion to the ramping demands caused by net load variations, load forecast deviations, and renewable energy forecast deviations. Specifically, for costs arising from renewable energy forecast errors, an allocation mechanism is designed based on the difference between the declared error range and the actual error. Second, within this allocation framework, hydropower and storage (including cascade hydropower and hybrid pumped storage) are utilized as flexible resources to mitigate wind power uncertainty and reduce its ramping costs. A two-stage day-ahead and real-time bi-level game model for wind–hydro-storage cooperative decision-making is developed. The upper level optimizes bilateral trading and market bidding strategies for wind–hydro-storage, while the lower level simulates the market clearing process. Through Stackelberg game modeling, joint optimal operation of wind–hydro-storage is achieved, ensuring mutual benefits. Finally, simulation results validate that the proposed ramping cost allocation mechanism can guide renewable energy to improve output controllability through economic signals. Furthermore, the bilateral trading and coordinated market participation of wind–hydro-storage realize win–win outcomes, reduce the ramping cost allocation for wind power by 23.10%, effectively narrow peak-valley price differences, and enhance market operational efficiency. Full article

In a bid to investigate the optimum transportation method for offshore wind-produced hydrogen (H₂) and assess the feasibility of repurposing the existing oil and gas infrastructure for H₂ transmission, this paper assesses the existing H₂ transportation methods with a comprehensive review of the H₂ impact on the existing natural gas pipeline infrastructure. To establish the possibility of repurposing the existing natural gas (NG) pipelines for H₂ gas transport, this paper reviews the influential technical measures—composition, pressure, temperature, volumetric energy density, density, and pressure drop—to assess whether the characteristics of hydrogen gas are compatible with the natural gas pipeline infrastructure. Based on these reviews, it was found that the current NG pipeline pressure exacerbates the H₂ embrittlement; for the existing NG pipelines to be repurposed, the operating pressure should be reduced, and the pipeline material should be revised. It was found that higher strength steels can be re-used with major modifications, or the pipeline should be constructed from material grade X52 or below. Nevertheless, the fitness of the existing NG pipelines for H₂ transmission should be assessed on a case-by-case basis and other factors such as erosion, leakage, pressure cycling, monitoring (e.g., distributed fiber-optic sensing technology) and a rigorous assessment of welds and joints should also be considered. Full article

Project-based organizations (PBOs) face persistent challenges in managing workload fluctuations that influence performance, competitiveness, and resource sustainability. Although previous research has explored bidding strategies and project inflows and outflows, few studies have systematically modeled workload-capacity dynamics or assessed policy responses to manage them effectively. To address this gap, this study develops a system dynamics (SD) model that integrates both pre-award and post-award project phases with internal and external organizational processes. Data for model development were drawn from the literature, industry reports, and expert interviews, resulting in the identification of 28 variables organized into subsystems covering demand, capacity planning, work execution, competitiveness, and financial performance. The model was validated through dimensional and structural tests, expert review, and further examined using social network analysis (SNA) and sensitivity analysis. The SNA results identified workload, production rate, and organizational capacity as the most influential variables. Sensitivity analysis conducted through Monte Carlo experiments, employing screening, regression, and ANOVA (analysis of variance) methods, revealed that capacity adjustment flexibility, minimum capacity, and demand level are critical factors influencing organizational stability. The validated model was then applied to evaluate policy alternatives under two distinct market conditions. Findings indicate that in lowest-price environments, a competitive, market-share-oriented policy enhances utilization and responsiveness, whereas in average-price markets, a stable capacity policy yields more sustainable outcomes. These results demonstrate how project-based organizations can strategically adjust bidding and capacity policies to stabilize workload dynamics and improve long-term operational resilience under different market conditions. The study contributes theoretically by extending the application of SD modeling to workload-capacity management in PBOs and contributes practically by offering a decision-support tool that helps managers assess capacity strategies, reduce risks, and align organizational policies with long-term sustainability objectives. Full article

Blockchain-based auctions often utilize smart contracts to automate auction rules, with much research focusing on enhancing privacy and fairness through cryptographic techniques. However, the authenticity of external data input into these systems is frequently overlooked. In particular, rational nodes may manipulate bidding data by submitting false types to maximize their utility, compromising market fairness and the reliability of auction outcomes. The aim of this study is to propose an alternative blockchain-based auction mechanism to incentivize nodes to report types honestly. We propose the Mixed-Node Advertising Auction (MNAA) mechanism for digital advertising auctions on blockchain systems. MNAA integrates quasi-linear and value maximization utility models to design allocation and pricing rules that eliminate nodes’ incentives to misreport their types, ensuring the authenticity of data submitted to the auction. To enhance efficiency, MNAA employs state channel technology and off-chain smart contracts, reducing main chain interactions. Theoretical analysis confirms that MNAA incentivizes truthful behavior and ensures security and correctness. Simulation results show that MNAA outperforms Generalized Second Price (GSP), Mixed Bidders with Private Classes (MPR), and Vickrey–Clarke–Grooves (VCG) auctions in terms of liquid social welfare (LSW), publisher revenue, and allocation efficiency, while also improving the transaction throughput and showing good performance in terms of transaction costs and latency. Full article

Building Information Modeling (BIM) has changed the landscape of the architectural, engineering, and construction (AEC) industry in recent decades. However, BIM is not well researched in most developing countries; in particular, few studies have addressed its adoption in Malawi. A non-probability, purposive sampling approach was adopted. A total of 143 questionnaires were completed. This research reveals that, while construction experts are aware of BIM, the level of uptake remains quite low. Architects in Malawi are the most knowledgeable, followed by land surveyors and then engineers. This research shows that most experts in Malawi are at level 1 of BIM usage, which is the first stage of BIM adoption and is characterized by the use of 3D models and output representation. Furthermore, the study results have shown that the Malawian AEC sector is currently succeeding at the modelling stage of maturity but is stalled by lack of collaborative frameworks, such as Integrated Project Delivery (IPD). Therefore, unless the industry shifts toward a unified Common Data Environment (CDE), advanced capabilities like clash detection will remain underutilized and disconnected from broader project success metrics. Statistical analysis has shown that the correlation analysis demonstrates a strong link (r = 0.75) between Integrated Project Delivery (IPD) and high BIM maturity, whereas traditional Design-Bid-Build methods show a critical misalignment with digital workflows. The study identifies high software costs and a lack of national standards as the primary barriers to adoption. Therefore, there is a need for robust sensitization to the benefits of BIM and training to improve its uptake in the context of Malawi’s construction industry. In order to advance Malawi’s BIM maturity, the research recommends a strategic shift toward integrated procurement models, the establishment of national BIM mandates, and the modernization of technical education to bridge the existing knowledge gap. Full article

Timber sale prices are influenced by multiple tract, product, and transaction characteristics. This study evaluates the effects of species composition, product class, sale method, harvest type, timber quality, and average tree diameter on timber stumpage prices using timber sale records from Alabama between 1 January 2010 and 31 December 2019. Prices were modeled on a per weight unit basis using a generalized linear model with a Gamma distribution and logarithmic link. Results indicate that larger average diameters were consistently associated with higher prices across most product classes. Harvest type also influenced prices, with salvage operations yielding prices approximately 8.3% lower than thinning operations. Timber quality had a moderate effect: good-to-excellent quality timber sold for about 4.8% higher prices than poor-to-fair quality timber. Sale method was an important determinant of price outcomes. Negotiated sales generated significantly lower prices than sealed-bid sales, averaging approximately 17% lower overall. However, interaction analysis revealed that negotiated sales produced higher prices for mixed hardwood sawtimber, likely reflecting the diverse end uses of these products. Regional effects were also evident, with higher prices observed in the southwestern portion of the state, likely due to proximity to the Port of Mobile and associated export markets. These findings highlight the importance of both tract and transaction characteristics in determining timber prices and provide guidance for landowners and forest managers when selecting sale strategies and management practices. Full article

Liver cancer is one of the most prevalent and lethal cancers worldwide, characterized by poor prognosis and limited treatment options. Triptophenolide (TRI), a diterpenoid compound, has shown anti-proliferative activity in breast and pancreatic cancers, but its role in liver cancer remains largely unexplored. In this study, TRI significantly inhibited the proliferation of HepG2 (hepatoblastoma) and HuH7 (hepatocellular carcinoma) cells in a dose-dependent manner, with IC₅₀ values decreasing from 279.9 to 229.4 µg/mL (24–48 h) in HepG2 and from 441.1 to 282.6 µg/mL in HuH7. Colony formation assays confirmed the suppression of HCC cell growth. TRI also promoted apoptosis, increasing apoptotic rates to 68.99% in HepG2 and 43.34% in HuH7 at 400 µg/mL (48 h). Cell cycle analysis revealed S-phase arrest, with TRI raising the S-phase population to 42.02% and 45.38%, respectively. Mechanistically, TRI upregulated pro-apoptotic genes (TP53, CASP3/9/10, BAX, BAK1, BID, BIM) and proteins, activating the mitochondrial apoptotic pathway. In vivo, TRI (10 mg/kg) markedly reduced tumor volumes in HepG2 and HuH7 xenografts compared with controls, without obvious systemic toxicity. These findings suggest that TRI exerts anti-proliferative, pro-apoptotic, and cell cycle regulatory effects in HCC. However, further preclinical studies are warranted to elucidate its mechanisms and evaluate its safety profile. Full article

Background: Despite mesalamine’s efficacy in mild-to-moderate ulcerative colitis (UC), many patients fail to achieve complete clinical or biochemical remission. Pentoxifylline (PTX) may act as an adjunct therapy by modulating cytokine production and oxidative stress. Aim: To evaluate the therapeutic effect of adding PTX in patients with UC. Methods: In this randomized, double-blind, placebo-controlled pilot study, 60 patients with UC were assigned to mesalamine plus placebo (Group 1) or mesalamine plus PTX 400 mg BID (Group 2) for 24 weeks. The primary outcome was changes in the partial Mayo score (PMS). Clinical remission was defined as PMS ≤ 2 with no subscore > 1; clinical response as a reduction in PMS ≥ 2 points. Quality of life (QoL) was measured using the Inflammatory Bowel Disease Questionnaire (IBDQ-32). Serum TNF-α, fecal calprotectin, and erythrocyte sedimentation rate (ESR) were assessed. Analyses were performed using intention-to-treat (ITT) and per-protocol (PP) approaches. Subgroup analyses stratified by prior mesalamine exposure, and multivariable regression adjusted for age, sex, disease duration, smoking, and disease extent. Results: PTX significantly improved PMS compared to placebo in both ITT and PP analyses. Clinical response and remission rates were higher with PTX. IBDQ-32 scores increased, and TNF-α, calprotectin, and ESR decreased significantly more with PTX. Improvements were consistent across mesalamine-naïve and experienced patients. Multivariable regression confirmed that these effects were independent of demographic or disease-related confounders. Conclusions: Adjunctive PTX significantly enhanced clinical outcomes, reduced inflammation, and improved QoL in UC patients, supporting its potential as an effective add-on therapy to mesalamine. Full article

Many construction tenders conducted by public institutions and organizations are canceled for various reasons, leading to project delays, resource inefficiencies, and disruptions to public services. This research aims to analyze the reasons for construction tender cancellations and the factors that influence the likelihood of cancellation, with a focus on institutional capacity and transaction costs. The cancelled tenders were obtained from the Electronic Public Procurement Platform (EKAP), which is officially used by public bodies. A total of 2483 construction tenders canceled in 2024 were analyzed. This figure represents 15.44% of the construction tenders conducted in Turkey in 2024. The construction tenders examined were subjected to a categorical frequency analysis using administrative reason codes. Additionally, weighted logistic regression was used to identify factors associated with the likelihood of cancellation among the 16,105 construction tenders held in 2024. According to the analysis results, region, type of administration, time, and tender type have a statistically significant impact on cancellation. The primary causes for cancellation include bids substantially above the estimated cost, the absence of submitted tenders, and the issuance of a published circular. The municipal elections held in March 2024 and the accompanying circular have led to an increase in tender cancellations. Inadequate institutional capacity may lead to uncertainty in the process; this, in turn, may result in the suspension of tenders and a rise in transaction costs. In this context, strengthening institutional resilience can be seen as a facilitator in resolving many issues. The factors that lead to tender cancellations and the suggested approaches can offer useful guidance for both the administration and contractors in normalizing processes. Furthermore, public authorities might consider investments to enhance institutional capacity to reduce the risk of tender cancellations. Full article