Search Results (201)

In large-scale plant construction projects, integrating Building Information Modeling (BIM) with construction schedules is essential for detailed planning and advanced practices such as Advanced Work Packaging (AWP), yet a granularity mismatch remains between schedule activities and object-level BIM components. This study proposes a method that combines lightweight axis-aligned bounding box (AABB) geometry with piping-specific semantic rules to derive object-level connectivity for installation grouping and sequencing. The method was implemented as a custom Autodesk Navisworks add-in and evaluated using an industrial process piping system comprising 705 physical objects. Geometric adjacency relationships were refined through semantic false-positive filtering, achieving 99.02% edge-level precision and 98.37% port-count agreement. The validated connectivity was then used to restructure 20 initial semantic partitions into 16 dimensionally feasible installation groups. A candidate installation sequence was subsequently generated by prioritizing equipment-connected main-line piping and maintaining continuity along connected piping routes. The results demonstrate that lightweight geometry combined with piping-specific semantic constraints can reliably support object-level installation planning without requiring predefined installation grouping or sequencing information in the BIM model. The proposed method provides an intermediate planning structure that links detailed BIM objects with broader construction schedule activities and supports subsequent detailed 4D BIM planning. Full article

Reliable determination of the surge limit of an installed centrifugal compressor cannot rely solely on OEM performance maps, theoretical predictions, or previously configured surge lines. The actual field boundary is influenced by installation-specific characteristics, including piping volumes, recycle-system dynamics, valve response, and instrumentation, all of which affect compressor behavior as surge is approached. At the same time, field surge testing is inherently demanding, because it is a safety-critical procedure that requires careful execution and often depends on the experience of specialist personnel. This paper presents a semi-automated supervisory framework for field surge limit verification intended for use by trained site engineers under operator supervision. The framework guides the testing process through readiness checks, instrumentation verification, recycle-valve assessment, gradual reduction of surge margin, real-time monitoring, surge-event identification, recovery actions, and structured data logging. Because early surge precursors are not consistently visible using standard plant instrumentation, the proposed approach relies on a practical signal-based event-recognition method derived from installed measurements and referenced to a pre-event baseline. The paper also introduces a structured method for tuning staged Recycle Trip^® recovery actions following surge limit verification using a limited number of field tests. The field evaluation included seven industrial compressor records: five independently confirmed surge cases, one shutdown/non-surge transient, and one confirmed no-surge case. Using a record-specific baseline threshold, all five confirmed surge events were recognized, with reported detection delays of 0–0.1 s. The supporting dynamic simulation environment was used for logic development and qualitative assessment of the supervisory and recovery-tuning concepts. Overall, the proposed approach provides a more structured and repeatable basis for supervised field surge limit verification while preserving operator authority. Full article

Hydraulic short-circuit (HSC) operation is an important approach to enhancing the operational flexibility of pumped-storage power plants (PSPPs). However, under this new operating mode, the flow characteristics in the bifurcated pipe deteriorate significantly, posing a threat to the efficiency of the piping system and potentially affecting the inflow conditions for the turbine. In this study, six improved bifurcated pipe models were designed, and their internal flows under pumping, generating, and HSC modes were numerically simulated. Entropy production theory and vortex identification method were employed for flow field analysis. The results show that local modifications confined to the bifurcation are insufficient to simultaneously improve energy characteristics across different modes. In contrast, the bypass pipe enables early flow diversion, weakening the original high-dissipation regions while introducing controllable additional losses. M6 achieves an average energy loss reduction of 47.85% in the mid-to-high flow split ratio range (FSR > 0.3). A strong correlation is observed between vortex suppression and energy loss reduction: the bypass pipe substantially shortens the main vortex length at the inlet section of the generating branch, while simultaneously inducing new shear vortices at the junction; adjustment of its installation position is expected to further shorten their extension, thereby ensuring the normal operation of the turbine. This study provides a new technical pathway for extending the operating range of HSC operation and contributes to enhancing the grid-regulation capability of PSPPs. Full article

Industrial tanks are key components of process plants. However, they are highly susceptible to foundation settlement under high operating loads. Therefore, reducing settlement is necessary to protect the tank and the associated piping. In this work, Finite Element Method (FEM) analyses were conducted to assess the effects of construction on adjacent pipelines in an industrial plant located on the eastern coast of Sicily (Italy). The biological basin has a longitudinal axis of symmetry and consists of two tanks. The geotechnical model was developed from geological and geotechnical investigations carried out in the investigated area. PLAXIS2D software (Bentley Systems) was employed to perform consolidation analyses. The findings show that the magnitude and application of loads play a key role in the estimated settlements, demonstrating the importance of including the load eccentricity in the analysis. The influence zone following the construction of the biological basin was derived to evaluate the potential impact on adjacent pipelines. Full article

Engineering schematics, such as electrical, mechanical, piping and instrumentation diagrams, record how industrial plants are built and operated, but most of them survive only as images or scanned sheets that software cannot read. Digitizing them by hand is slow and error-prone: an expert must find and classify hundreds of symbols, read dense technical text, and work out which label belongs to which component. Progress with learning-based methods has been held back on two fronts at once. There are almost no annotations that connect a text label to its symbol, and the drawings themselves are usually confidential, so even unlabeled sheets rarely reach the public domain. We address this with a system that turns a drawing into a structured, queryable graph: it detects and classifies the graphical components with an object detector, recovers the technical text, and then resolves which label belongs to which component. Our contributions are threefold: (i) the first at-scale dataset of manually annotated text-to-symbol links for industrial schematics; (ii) a complete, deployable digitization system combining tiled detection with sliced inference, off-the-shelf OCR, and a text-to-symbol association stage; and (iii) a rigorous, leakage-free benchmark of association methods. Under an observable-only candidate protocol, we find that on logic circuits association is dominated by geometry: a simple pairwise model reaches about 99% top-1 and a graph neural network matches but does not exceed it, whereas the denser P&IDs still benefit from a geometric rule-based chain. Detection reaches an mAP@50 of 0.995 on logic circuits and about 0.91 across the 107-class P&ID taxonomy. The system produces a partial semantic graph; connecting lines and flow direction are not extracted. Full article

To address the limited pumping-mode flexibility of fixed-speed pumped-storage units, this paper presents a simulation case study of a one-pipe–two-unit parallel ternary system developed in OpenModelica and coupled with Python 3.7. The study examines pure charging and generation, hydraulic short-circuit (HSC) charging, and the PID control-activation transient at nominal speed. A 50 MW benchmark reproduces published pump and turbine shaft powers to within approximately 0.5%, while the system-efficiency difference is 0.14 percentage points, supporting implementation consistency; no plant-measurement validation is claimed. Dual-pump operation reduces the charging time by approximately 44% relative to single-pump operation but lowers efficiency, whereas dual-turbine operation is slightly more efficient because of improved per-unit flow matching. Across the full-cycle HSC sweep, average efficiency increases from 38.6% at 40 MW to 74.1% at 90 MW as internal recirculation decreases. In the PID sensitivity screen, the proportional gain k has the largest effect on the response, a small integral time T_i amplifies sensitivity to k and can increase overshoot or hydraulic loading, and the derivative coefficient w_d has only a minor effect within the tested range. The numerical bounds are specific to the selected characteristic maps, reservoir, and waterway; the results are intended as retrofit-screening guidance rather than universal design limits. Full article

External safety-related piping in nuclear power plants may be exposed to tornado missile impact, resulting in local indentation, global bending deformation, and transient support responses, which may threaten the structural integrity and safety functions of nuclear power plants. Existing pipe impact studies have mainly focused on failure behavior under idealized or prescribed boundary conditions, while the application of viscous damper supports remains limited. In this study, a three-dimensional nonlinear finite element model of a pipe-support system is established in Abaqus. The model is used to investigate the effects of support type, damper parameters, support stiffness ratio, pipe span, and wall thickness on impact response and energy dissipation. The results show that support flexibility accounts for the major reduction in global bending relative to rigid supports, while viscous dampers further reduce support displacement and velocity and provide additional energy dissipation. In the benchmark case, the viscous damper support reduces peak global bending by 78.9% compared with the rigid support, and reduces peak support displacement and velocity by 55.6% and 54.5%, respectively, compared with the elastic support. Its influence on local indentation remains limited. These findings indicate that viscous damper supports mitigate impact responses primarily by controlling support motion and altering the energy dissipation behavior of the pipe–support systems, rather than by directly suppressing local indentation. This study provides a reference for support layout and parameter selection of external safety-related piping subjected to tornado missile impact. Full article

Remote-controlled UAS-based soil sampling offers great potential for scientific research and practical applications in various fields, including agriculture, environmental monitoring, hazardous waste, radiation measurements, chemical plants, snow sampling and glaciology. The added value of automated sampling using a UAS (unmanned aircraft system) compared to manual sampling lies primarily in improved accessibility to hazardous or remote locations, increased operational safety, and the potential to improve efficiency in applications requiring repeated or difficult-to-access sampling. This article introduces two different 3D-printed constructions (grab arm and screw pipe) for UAS-based, remote-controlled sample collection of different soil types. The grab arm construction is based on an adapted version of an open-source CAD from GrabCAD. The screw pipe construction is a new design. During an expedition to Greenland in August 2025, the two constructions were manually evaluated during several days of field work near the Danish and Austrian research stations at the Sermilik Fjord to assess their mechanical sampling performance on challenging Arctic surface materials, including dry and wet sand, gravel, glacial sediment, snow, and glacier surfaces. Because flight testing was not possible during the expedition due to unavailable UAS batteries, these experiments were limited to manual ground evaluation of the constructions. Independent flight tests were subsequently conducted in Austria using a DJI Matrice 300 to evaluate the integration of both the grab arm and the screw pipe with the UAS platform and their operational handling during flight. In Greenland the performance of manual sampling was documented precisely. Further the coordinates of each sampling point were recorded by using GPS, sample images were taken on site, and the collected material was weighed. The results show that UAS in combination with 3D printed constructions is a flexible and location-independent solution for obtaining soil samples of varying composition. In addition to the design, materials, and electronics of the systems, the article also describes the connection to the UAS and the field work results. Full article

Corrosion in carbon steel piping systems is a critical issue in hydroelectric power plants, as progressive wall thickness loss may compromise integrity and operational reliability. This study proposes a data-driven framework combining descriptive statistical analysis and distinct clustering methods to map and rank corrosion conditions in water pipeline systems of a hydroelectric power plant in Brazil. A total of 4916 pipe segments from 20 generators (generating units 1 and 2) were evaluated and the feature matrix included wall loss descriptors, measured thickness statistics, minimum allowable thickness, wall integrity indicators, pipe geometry, segment type, and system information. Descriptive analyses revealed heterogeneous corrosion patterns across generating units, segment types, diameters, and inspection points, with localized severe wall loss conditions in specific segments. A principal components analysis was applied to reduce the original feature space while preserving approximately 80% of the cumulative variance, as suggested by the literature. The best clustering solution was obtained using a weighted consensus model based on the Calinski–Harabasz index, resulting in five degradation/integrity profiles that support segment-level corrosion ranking and inspection prioritization. The proposed framework provides a structured basis for integrating inspection data, statistical descriptors, and integrity indicators into maintenance and decision support processes for hydroelectric power plant piping systems. Full article

Precise station-keeping of construction barges during offshore operations remains a demanding control problem because the underlying dynamics are highly nonlinear and the disturbance environment is seldom known a priori. This work investigates how a learning-based controller can be embedded into the coordinated winch-control architecture of a specialized engineering vessel to deliver accurate positioning in shallow water. Vessels such as rock-dumping platforms and pipe-laying barges routinely rely on a spread of mooring lines to hold station, and the tensions on these lines are, in current industrial practice, still adjusted manually by the winch operator. The scheme proposed here replaces that manual loop with an adaptive neural feedback law synthesized through backstepping, allowing the unknown portions of the ship model and the exogenous environmental loads to be compensated online without requiring prior identification. The 3DOF control wrench produced by the feedback law is then mapped to the physical line tensions through a constrained allocation that respects the unilateral and breaking-load constraints of the spread. The closed-loop system is shown to be semi-globally uniformly ultimately bounded (SGUUB) in the Lyapunov sense, and its performance is benchmarked against a conventional PD regulator and a nominal model-based design through simulation of a full-scale rock installation barge. When the model-based baseline is given the nominal plant, it attains the cleanest tracking; the proposed neural law achieves comparable steady-state accuracy without requiring prior identification of the hydrodynamic coefficients. A model-free deep reinforcement learning (PPO) controller is additionally benchmarked under irregular (JONSWAP) seas; it attains bounded sub-metre station-keeping without any model knowledge, on par with the PD baseline but less precise than the model-based and adaptive-neural laws. Full article

Providing optimal temperatures in greenhouses is essential for cultivating high-temperature-demand crops in winter. Therefore, this study aimed to investigate the feasibility of utilizing a flat plate solar collector (FPC) for heating greenhouses. A field experiment was conducted, complemented by simulations using the PolySun V2023.11 software. The FPC system comprised two collectors, each with an aperture area of 2.24 m², connected to a 300 L hot water tank. The water tank had an internal electric backup heater (2 kW) and a thermostat to regulate the hot water temperature. The experiment consisted of two greenhouses, each with an area of 50 m². The first unheated greenhouse (UHGH) was used as the control, while the second heated greenhouse (HGH) was heated by a closed-loop system comprising copper pipes installed along the internal perimeter. Results revealed that the FPC significantly increased air temperature by 2.7 °C, and reduced relative humidity by 9.7% in the HGH compared to the UHGH. Simulated results showed that the annual generated energy of the FPC was 4830 kWh with a reduction of CO₂ emission by ≈2.9 tones. The average thermal efficiency of the FPC was 44%, with a payback period of 8.5 years. In conclusion, the FPC could protect plants from low temperatures in winter. Full article

Pressurized pipelines are critical components in hydraulic engineering systems, including urban water supply networks and hydroelectric power plants. These systems are susceptible to air entrapment during operations such as filling and emptying, which can reduce the effective flow area and trigger critical pressure surges or sub-atmospheric conditions. One-dimensional approaches, namely the Rigid Water Column (RWC) and Elastic Water Column (EWC) models, are the most widely used due to their balance between physical accuracy and computational practicality. EWC models have been widely used to analyze transient phenomena in pipe filling and water hammer processes; however, their application to emptying operations is limited. For this reason, this study develops an EWC-based formulation for emptying operations and assesses pressure behavior through a dimensionless analysis for different air pocket configurations. The developed model couples the Method of Characteristics (MOC) with a polytropic air pocket model, enabling the representation of wave propagation effects that RWC-based models cannot capture. The formulation is verified against 24 experimental cases, yielding a mean absolute error of 0.35% in minimum pressure prediction. The results show that dimensionless air pocket ratios $x_0/L_T$ between 0.17 and 0.83 produce minimum pressures between 0.309 and 0.877 $p_{atm}^{*}$, confirming that smaller initial air pocket volumes generate the most severe depressurization conditions. The inclusion of an air valve in the most critical scenario effectively prevents sub-atmospheric pressure development, underscoring the protective role of air admission devices. These findings provide a dimensionless framework for characterizing transient pressure risk during pipeline emptying across different operational conditions. Full article

Coal-fired power units remain integral to electricity supply in many regions while facing increasingly stringent environmental expectations. Bridging reliable generation with sustainability requires more than end-of-pipe controls; it demands continuous intelligence embedded in plant operations. This study introduces an industry-oriented monitoring framework that transforms historical operational records into actionable foresight, enabling on-the-fly orchestration of combustion conditions to anticipate sulfur oxide (SOx) concentrations. Leveraging 919 empirical data points collected in 2019 from Unit 8 of the Taichung Thermal Power Plant, the framework integrates robust data governance, targeted feature curation, and a neural network-based analytics core. Eight process variables—sulfur content, coal feed rate, fixed carbon, grinding rate, calorific value, excess air, air flow, and boiler efficiency—emerge as the most influential drivers through systematic selection and feature importance attribution. The resulting forecasting module exhibits near-perfect alignment with observed emissions (R² = 0.99), enabling near-real-time guidance for setpoint adjustments and facilitating compliance strategies under varying load and fuel-quality conditions. Beyond accuracy, the system is architected for scalability and portability, aligning with Industry 4.0 paradigms by coupling continuous sensing, data-driven decision support, and stakeholder transparency. By reframing emission oversight as a proactive, intelligent service rather than a static reporting function, the proposed approach advances operational resilience, regulatory compliance, and community trust, with direct implications for resource efficiency and circular economy initiatives across heavy industry. The framework reduces potential SOx emissions and improves energy utilization efficiency under varying operational conditions. This approach contributes to environmental sustainability by enabling proactive emission reduction and cleaner production practices. It supports regulatory compliance and aligns with global sustainability goals, including SDG 7 and SDG 13. Full article

Aquaponic systems are increasingly recognized as sustainable technologies for integrated fish and vegetable production. However, concerns remain regarding the potential internalization of human pathogens into vegetables grown in these systems. This study assessed the risk of pathogen internalization in lettuce leaves grown in aquaponic systems with Nile tilapia challenged with Escherichia coli or Vibrio cholerae. The system comprised nine fish tanks, eighteen hydroponic pipes, and eighty-one lettuce plants, with tanks assigned to three treatments. Samples of water, fish gut, fish blood, and lettuce leaves were collected. Microbiological analyses included selective culture, biochemical assays, and molecular identification. Although colonies consistent with E. coli and V. cholerae were recovered on selective media, molecular sequencing identified other bacterial species, including Aeromonas sp., Aeromonas caviae, Aeromonas veronii, Enterobacter hormaechei, and Citrobacter freundii. The findings indicate that conventional culture-based methods may produce false-positive results and highlight the importance of molecular confirmation. Notably, pathogenic bacteria associated with tilapia were detected and appeared capable of disseminating through the system and internalizing into lettuce tissues. This result highlights the need for biosecurity measures, contamination monitoring, and the combined use of conventional and molecular diagnostic tools to ensure accurate pathogen detection and compliance with international food safety standards. Full article

The adoption of photovoltaic (PV) energy in irrigation is rapidly increasing, supported by a range of available technologies. However, an agronomic perspective that could help overcome inherent limitations of PV systems remains absent. In fact, current irrigation design methods do not explicitly take into account the dynamic nature of PV power generation. While irrigation engineering conceptualises soil as a reservoir for plant-available water, it can also function as an energy reservoir, storing solar-derived energy in the form of soil moisture for subsequent crop use. Building on this concept, this study proposes an integrated framework for designing off-grid PV irrigation systems based on asymmetric irrigation sectors. The framework couples hydrological, agronomic, and energy components to synchronise solar energy generation with crop water requirements, thereby eliminating the need for intermediate energy storage. The methodology was applied to two case studies: a hedgerow olive orchard and an almond orchard in southern Portugal, both with drip irrigation. Results demonstrate that the asymmetric-sector design provides a technically feasible and low-complexity solution for integrating photovoltaic energy into irrigation systems. The conventional irrigation system required 1.42 kW of minimum pumping power for olive orchards and 1.32 kW for almond orchards. The dimensions of the main lines ranged from 97.8 mm for olive and 75 mm for almond orchards, while the flow rate of the emitter was 2.3 L h⁻¹ for olive and 3 L h⁻¹ for almond orchards. Although PV-compatible operation required hydraulic adjustments including increases in design flow rate (226–255%), pump power demand (87.5–241%), and pipe diameters (up to 120% in olive and 75% in almond), these adaptations enable irrigation systems to operate under the variability inherent to solar-based energy supply. This hydraulic oversizing leads to higher initial investment costs; however, this can be mitigated to a certain extent by diminished operating costs and complete energy autonomy from the electricity grid. Full article