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Beyond Binary Edits Robust Multimodal Knowledge Editing with Adversarial Subspace Alignment Agentic Proving for Program Verification MemAudit: Post-hoc Auditing of Poisoned Agent Memory via Causal Attribution and Structural Anomaly Detection OpenSkillEval: Automatically Auditing the Open Skill Ecosystem for LLM Agents One Policy, Infinite NPCs: Persona-Traceable Shared RL Policies for Scalable Game Agents How Human-Like Are Large Language Models? A Register-Aware Linguistic Evaluation Framework Benchmarking Google Embeddings 2 against Open-Source Models for Multilingual Dense Retrieval and RAG Systems Structure-Guided Entity Resolution: Fine-Tuning LLMs for Robust Name Matching in Complex Linguistic Contexts Solving the Aircraft Disassembly Scheduling Problem Co-ReAct: Rubrics as Step-Level Collaborators for ReAct Agents CP or DP? Why Not Both: A Case Study in the Partial Shop Scheduling Problem Asking For An Old Friend: Diagnosing and Mitigating Temporal Failure Modes in LLM-based Statutory Question Answering EDGE-OPD: Internalizing Privileged Context with Evidence Guided On-Policy Distillation ARES: Automated Rubric Synthesis for Scalable LLM Reinforcement Learning SSDAU: Structured Semantic Data Augmentation for Joint Entity and Relation Extraction Naturalistic measure of social norms alignment Articulatory strategy as a source of variation in acoustic vowel dynamics When Planning Fails Despite Correct Execution: On Epistemic Calibration for LLM-Based Multi-Agent Systems EquiSumm : A Gender Bias-Aware Framework for Inclusive Tweet Summarization Metacognition as Reward: Reinforcing LLM Reasoning via Knowledge and Regulation Signals From Correctness to Preference: A Framework for Personalized Agentic Reinforcement Learning Cultural Adaptation in Large Language Models for Political Discourse Emotion Recognition in Sign Language Conversation ClimateChat-300K: A Multi-Modal Facebook Dataset for Understanding Diverse Perspectives in Climate Communication AraHopeCorpus: Annotation Guidelines and Dataset for Hope Speech in Arabic Social Media Crisis Discourse Human-in-the-Loop Multi-Agent Ventilator Decision Support with Contextual Bandit Preference Learning Convergence Without Understanding: When Language Models Agree on Representations but Disagree on Reasoning DART: Semantic Recoverability for Structured Tool Agents Ontological Knowledge Blocks: Executable Compliance and Profile-Based Validation for Trustworthy AI Systems Parallel Context Compaction for Long-Horizon LLM Agent Serving
Optimization Models and Steady-State Minimum-Fuel Operati...
[Submitted on 12 Jun 2026] · 2026-06-15 · via cs updates on arXiv.org

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Abstract:This paper presents an optimization framework for the operation of hydrogen-based hybrid electric aerospace propulsion systems consisting of a hydrogen gas turbine and an electric motor powered by a solid oxide fuel cell, connected to the gas turbine via multiple gas channels and heat exchangers. Our framework computes the minimum-fuel optimal operating strategies over a flight mission accounting for the complex propulsion system with strong thermodynamic and mechanical coupling between components. First, we identify surrogate optimization models of the components employing high-fidelity model simulations. Second, we frame the minimum-fuel optimal control problem over a given flight mission and parse it into a static nonlinear optimization problem that can be efficiently solved with off-the-shelf nonlinear programming algorithms. Finally, we apply our optimization framework to a typical flight mission of an advanced, commuter aircraft (Beechcraft 1900D market segment), considering a parallel propulsion system architecture with four different configurations that share a common baseline but differ in the inclusion of an additional battery and by-pass valves around the two heat exchangers. The resulting optimal trajectories are validated against high-fidelity simulation results, demonstrating the accuracy of our framework. Results show that adding by-pass valves around the air and hydrogen heat exchangers can reduce fuel consumption by 19.11 % without the battery, and by 19.56% with the battery. We show that adding a battery yields a slight increase in fuel consumption (below 1%) for future projected energy densities under steady-state conditions. Conversely, when considering state-of-the art energy densities, the additional battery weight outweighs the benefits, limiting its potential applicability to only assisting transients, which are not considered in the present work.

Submission history

From: Uto Perra [view email]
[v1] Fri, 12 Jun 2026 14:15:45 UTC (448 KB)