Solid-particle erosion at pipeline elbows threatens the integrity of oil-and-gas transport systems. This numerical study used the Euler–Lagrange discrete phase model and the Finnie erosion model in ANSYS Fluent to compare a single 90° elbow, two 45° elbows, and three 30° elbows for water–sand flow at inlet velocities of 10–40 m/s and particle diameters of 0.0002–0.0005 m. Two output measures are reported: contour plots show the local cellwise maximum wall erosion rate, whereas line graphs show the area-weighted mean wall erosion rate. At the reference condition of 40 m/s and a particle diameter of 0.0005 m, the area-weighted mean rates were 5.18 $\times$ 10$^{-5}$, 2.89 $\times$ 10$^{-5}$, and 3.59 $\times$ 10$^{-5}$ kg m$^{-2}$ s$^{-1}$ for the single 90° elbow, two 45° elbows, and three 30° elbows, respectively. Relative to the single elbow under the same simulation conditions, the mean erosion rate decreased by 44.2% with two 45° elbows and by 30.7% with three 30° elbows. The corresponding local contour maxima were 3.17 $\times$ 10$^{-3}$, 2.82 $\times$ 10$^{-3}$, and 2.59 $\times$ 10$^{-3}$ kg m$^{-2}$ s$^{-1}$. These results show that distributing the change in flow direction across multiple elbows reduces severe particle–wall impacts, with two 45° elbows providing the lowest area-weighted mean erosion rate.

Transit-oriented development (TOD) offers a planning basis for compact, mixed-use, and vibrant station areas. However, in many rapidly developing Chinese cities, metro-network expansion has not been matched by coordinated station-area commercial renewal, resulting in spatially uneven street-level activity despite improved transit accessibility. Taking the North Ring Road Station area in Changchun, China, as a case, this study examines the associations between TOD-related spatial conditions and observed human activity intensity as a proxy for commercial spatial vitality, and how these spatial associations can inform targeted regeneration strategies. Within an 800 m TOD analytical boundary, commercial point of interest (POI) data, Baidu Heatmap-derived human activity data, building footprints, road-network data, land-use information, and field observations were integrated. Average nearest-neighbor (ANN) analysis, kernel density estimation (KDE), standard deviational ellipse (SDE) analysis, ordinary least squares (OLS) regression, and geographically weighted regression (GWR) were applied within a 5D TOD framework. The results reveal a dual-core, corridor-oriented, and spatially uneven commercial structure. Commercial facility agglomeration and functional diversity are positively associated with observed activity intensity, whereas transit distance, road-network configuration, building morphology, and proximity to commercial anchors exhibit spatially heterogeneous associations. These results suggest that transit proximity and commercial concentration alone do not necessarily correspond to spatially continuous activity when pedestrian permeability, interface openness, and functional mixing are limited. The study translates these associations into evidence-informed transport-development responses that coordinate metro-entrance access, pedestrian transfer and first/last-mile connections, commercial functions, and surrounding land uses, thereby providing a micro-scale diagnostic approach to station–street–commercial integration.

Selecting an appropriate antihypertensive drug class for older patients with multimorbidity requires multiple clinical considerations to be evaluated simultaneously, including comorbidity-specific suitability, treatment-related risks, therapeutic priorities and professional judgement. A transparent decision-support framework is therefore needed to structure these heterogeneous considerations without implying that a mathematical ranking constitutes a clinical recommendation. An entropy-weighted group decision-support framework was developed and evaluated using a hypothetical 72-year-old patient with multiple comorbidities. Seven antihypertensive drug classes—diuretics, beta-blockers, Angiotensin-Converting Enzyme (ACE) inhibitors, Angiotensin II Receptor Blockers (ARBs), calcium-channel blockers (CCBs), alpha-1 blockers and central alpha-2 agonists—were assessed against eight criteria: physician experience, suitability for older patients, suitability for patients with diabetes, suitability for patients with kidney disease, suitability for patients with congestive heart failure, suitability for patients with a history of myocardial infarction, medication-related complication risk and rapidity of therapeutic effect. Assessments were provided independently by an internist, a cardiologist and a urologist. Criterion weights were derived using the entropy method from transformed rank-score distributions, while rank-frequency linear assignment and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) were used to aggregate expert assessments and obtain alternative rankings. ARBs were ranked first by TOPSIS and third in both optimal linear-assignment solutions. Two equally optimal linear-assignment solutions were obtained, with beta-blockers and alpha-1 blockers exchanging the first and sixth positions. Central alpha-2 agonists were ranked last by both approaches. Importantly, the complete and tie-free rankings provided by every expert resulted mathematically in identical entropy weights of 0.125 for all eight criteria, indicating that criterion differentiation was not achieved under the adopted elicitation format. The resulting rankings therefore represent methodological outputs rather than evidence of clinical superiority among antihypertensive drug classes. The framework provides a transparent means of structuring multi-criteria and multi-expert assessments in complex clinical scenarios, while its preliminary nature, limited expert panel and absence of patient-level validation preclude direct clinical application. Validation using larger and more diverse expert panels, clinically validated criteria and patient-level outcomes is warranted before the framework can be considered for clinical decision-support applications.

Geothermal brine retains considerable thermal energy before reinjection, but its potential for additional power generation is not always fully utilized. Low-temperature solar preheating offers a possible route to increase heat recovery without altering the geothermal source conditions. This study investigates the integration of a field-tested trickle solar collector as a preheater for a small-scale geothermal organic Rankine cycle (ORC), with particular attention to energy performance, exergy efficiency, heat-transfer feasibility, and working-fluid selection. A thermodynamic model was developed using experimental collector data and a geothermal brine stream entering at 188 ℃ and leaving at the 90 ℃ reinjection limit. The brine mass flow rate was fixed at 1.690 kg/s, corresponding to a pinch-feasible 100-kW n-pentane reference cycle. Heat-transfer feasibility was evaluated over the complete counter-current temperature profile using a minimum approach temperature of 10 K. The tested collector produced an average useful heat output of 752.4 W per module and reached a maximum outlet temperature of 51.5 ℃. A field of 88 modules, with a total aperture area of 91.52 m$^2$, supplied 45.024 kW of useful solar heat to the preheater. For the n-pentane cycle, solar preheating increased the net power output from 100 to 106.473 kW while the thermal efficiency remained at 14.377%. The exergy efficiency increased from 51.393% to 53.705%, and the minimum temperature approach remained feasible at 10.120 K. Under the same brine and pinch constraints, R245fa produced the highest net power of 110.961 kW, closely followed by R1233zd(E) at 110.547 kW. Preliminary heat-exchanger sizing yielded a logarithmic mean temperature difference of 12.757 K, a UA value of 3.529 kW/K, and a required heat-transfer area of 7.06–11.76 m$^2$. The results indicate that trickle collectors are better suited to low-temperature preheating than direct ORC evaporation. This integration provides a technically feasible approach to increasing power recovery from geothermal brine while maintaining the original reinjection temperature and thermodynamic operating limits.

Urban development and management (UDM) plays a central role in addressing the environmental, social, and governance challenges associated with rapid urbanization. Although bibliometric studies have examined specific areas of urban research, the broader intellectual structure and long-term thematic development of UDM remain fragmented across multiple research streams. This study investigates the evolution, knowledge structure, and emerging research directions of UDM through a large-scale bibliometric and science-mapping analysis. A dataset of 40,435 journal articles and reviews published between 1925 and 2025 was retrieved from Scopus and analyzed following the Scientific Procedures and Rationales for Systematic Literature Reviews (SPAR-4-SLR) protocol. Performance analysis, co-citation analysis, bibliographic coupling, keyword co-occurrence analysis, and thematic mapping were conducted using bibliometrix and VOSviewer. The results showed a marked acceleration in research output, with 45.9% of all documents published during 2021–2025. The dataset accumulated 1,285,702 citations, averaging 31.8 citations per document. China recorded the largest publication output (9,309 documents), whereas the United States received the highest total citations (348,371) and h-index (223). Journal co-citation patterns revealed a multidisciplinary knowledge base centered on environmental and water sciences, while country-level bibliographic coupling showed a core–periphery structure organized around China, the United States, and Europe. Sustainable development and urban planning emerged as broad foundational themes, whereas water management occupied a central and well-developed position. The science-mapping results further identified climate adaptation, blue–green infrastructure, nature-based solutions, and digitally enabled urban management as prominent recent research directions. These findings demonstrate how UDM has developed from a predominantly planning- and growth-oriented field into a multidisciplinary research domain increasingly concerned with environmental limits, climate resilience, and data-supported urban governance. The study provides an integrated knowledge map of UDM and identifies research priorities concerning the Global South, sustainability measurement, blue–green infrastructure, climate–health interactions, digital urban management, circular urban systems, and urban governance.