DC Optimal Power Flow (DCOPF) is widely utilized in power system operations due to its simplicity and computational efficiency. However, its lossless, reactive power-agnostic model often yields dispatches that are infeasible under practical operating scenarios such as the nonlinear AC power flow (ACPF) equations. While theoretical analysis demonstrates that DCOPF solutions are inherently AC-infeasible, their widespread industry adoption suggests substantial practical utility. This paper develops a unified DCOPF -> ACPF pipeline to recover AC feasible solutions from DCOPF-based dispatches. The pipeline uses four DCOPF variants and applies AC feasibility recovery using both distributed slack allocation and PV/PQ switching. The main objective is to identify the most effective pipeline for restoring AC feasibility. Evaluation across over 10,000 dispatch scenarios on various test cases demonstrates that the structured ACPF model yields solutions that satisfy both the ACPF equations, and all engineering inequality constraints. In a 13,659-bus case, the mean absolute error and cost differences between DCOPF and ACOPF are reduced by 75% and 93%, respectively, compared to conventional single slack bus methods. Under extreme loading conditions, the pipeline reduces inequality violations by a factor of 3 to 5.
In this paper, a Hybrid High-Order (HHO) framework is developed for the Helmholtz equation with a spatially varying wave number and mixed Dirichlet–Neumann boundary conditions. A discrete Gårding-type inequality is established, leading to stability under the resolution condition ∥κ2∥L∞h2≲1, which is less restrictive in its dependence on the wave number than the classical κ3 h2 ≲ 1 condition often required in low-order finite element methods. Optimal error estimates are derived in both the energy norm and the L2-norm, achieving convergence rates of order k+1 and k+2, respectively, for sufficiently smooth solutions. The method is implemented on general polygonal meshes and incorporates static condensation for efficiency. Numerical experiments validate the theoretical results and demonstrate the method’s flexibility in handling variable coefficients and mixed boundary conditions, including Robin-type boundaries.
Maximum lateral acceleration (LAmax) reflects the peak lateral demand during curve negotiation and is relevant to driving comfort and vehicle-control stability. This study examined how driver characteristics, traversal-level variables, and roadway geometry influence LAmax during daytime and nighttime driving on mountainous roads. Data from 70 licensed drivers were collected using a high-fidelity simulator replicating a 22 km mountainous road, comprising 37,563 daytime and 35,460 nighttime curve-level observations. A unified Gamma-log generalized linear mixed-effects model (GLMM) with a participant-specific random intercept was estimated using daytime as the reference condition and Nighttime × Predictor interactions. Drivers with more than 10 years of experience showed lower expected LAmax, whereas those travelling more than 1000 km per month exhibited higher LAmax. At the traversal level, the normalized curve sequence was negatively associated with LAmax, whereas speed at its occurrence showed a positive association, with both effects differing by driving conditions. Long preceding tangents and medium-long curves were associated with higher LAmax, while gradient and radius exhibited non-linear, category-specific associations, several of which varied under nighttime driving. Preliminary empirical thresholds classified daytime observations into Comfort (≤1.79 m/s2), Moderate Comfort (1.79–3.91 m/s2), and Discomfort (>3.91 m/s2), and nighttime observations into Comfort (≤1.51 m/s2), Moderate Comfort (1.51–3.33 m/s2), and Discomfort (>3.33 m/s2). Using these thresholds, an exceedance-based assessment was conducted to quantify discomfort exposure between conditions and showed a higher proportion of Discomfort-category observations at night. The findings provide a framework for screening curve segments and supporting comfort-aware roadway evaluation and driver-assistance applications on mountainous roads.
A series of ruthenium meso-aryl dipyrrinato complexes namely, [(p-R-C6H4)C(C4H3N)2Ru(p-cymene)Cl] [where, R = t-Bu (1a), C6H5 (1b), Br (1c), OMe (1d)] provide an efficient atom-economical single step access route to bioactive pyrimidines (2−20) (19 examples) from primary and secondary alcohols and amidines proceeding via dehydrogenative coupling of alcohols followed by selective C−C bond formation. The mass spectrometric and 1H NMR evidences corroborated the presence of ketone and aldehyde bound ruthenium hydride species, [(p-R-C6H4)C(C4H3N)2]Ru(p-cymene)(PhCOCH3)(H) (B)−1(a−d) and [(p-R-C6H4)C(C4H3N)2]Ru(p-cymene)(PhCHO)(H) (F)−1(a−d), in a proposed catalytic cycle. To rationalize the experimental findings and advance the understanding of ruthenium-catalyzed dehydrogenation, density functional theory (DFT) calculations were performed on the ruthenium meso-aryl dipyrrinato (1d) complex to elucidate the catalytic pathway. Mechanistic studies reveal that the orientation of carbonyl oxygen and the hydride-transfer pathway govern alcohol dehydrogenation, while Non-covalent interaction (NCI) analysis elucidates the interactions responsible for this behavior. β-hydride elimination from alcohol represents the key kinetic bottleneck in the reaction pathway.
Biogas separation is essential for producing high purity CH4 as a clean fuel while enabling CO2 capture within carbon capture, utilization and storage (CCUS). However, insufficient separation can result in methane losses and incomplete CO2 capture, undermining climate benefits by high impact CH4 emissions with continued CO2 release. Hydrate based gas separation (HBGS) can be a potential solution for this purpose. The successful application of hydrate-based biogas storage depends on resolving the challenge of slow formation kinetics by developing methods that can effectively accelerate hydrate onset and growth. Thermodynamic additives (Tetrahydrofuran (THF), Cyclopentane (CP), 1,3 Dioxolane (DIOX) [forming sII structure] and Tetrabutyl methyl ether(TBME) [forming sH structure] at their stoichiometric concentrations alongside combinations with kinetic additives were employed to separate 24.8 mol% CO2 / 74.2 mol% CH4 (biogas) mixture at 4.7 MPa and 283.2 K. Dimethyl sulfoxide (DMSO) and piperazine were also tested in combination for their effect on formation kinetics and separation efficiency. Highest gas uptake of 102.72 +/- 5.12 mmol/mol was obtained using 2.86 mol% TBME with 0.1 wt% l-leucine. Selective separation ability of TBME forming sH hydrate was found to be higher compared to THF, CP and DIOX (structure sII hydrates) as it demonstrated highest separation factor of 2.45 +/- 0.1, employing 2.86 mol% TBME with 5 wt% piperazine. DIOX sII mixed hydrate showed better performance compared to THF and CP in terms of gas uptake and rate of hydrate formation specifically in combination with l-methionine. Dissociation study of mixed hydrates with morphological observations show case higher thermodynamic stability of CP compared to THF and DIOX, other sII promoters. Overall, this work provides the systematic comprehensive evaluation of sII and sH promoters integrated with different bio-additives, advancing HBGS as a viable strategy for simultaneous methane enrichment and CO2 capture with reduced environmental impact aligning with United Nations sustainable development goals (SDGs) of 7 and 13.
