arXiv subjects

Mansoorali Amiri

Publications and source records attributed to Mansoorali Amiri.

2 recordsLinked to original sources

arXiv2026

A Trans-Domain Digital Twin for Bio-Aware Control of Climate and Energy in Cattle Fattening Barns Using Single-Episode Optimizer Learning

In closed cattle-fattening barns, the indoor climate and herd growth are mutually interdependent. Temperature, relative humidity, airflow, and ventilation affect thermal comfort, feed intake, metabolic heat production, daily growth, feed efficiency, and energy consumption, while body-weight gain alters the future heat and moisture loads of the barn and, consequently, its ventilation, heating, and energy requirements. This article proposes a trans-domain digital twin framework with single-episode learning capability, customized for bio-aware climate and energy control in a closed cattle-fattening barn. The framework integrates a mechanistic climate simulator, a livestock growth simulator, model predictive control, lightweight reinforcement learning, and structured knowledge memory within a multi-rate temporal-loop architecture. The fast temporal loop operates every five minutes to evaluate actuator decisions and maintain short-term thermal comfort, safety, and energy efficiency, whereas the slow temporal loop provides biological guidance based on daily climatic conditions, feed efficiency, heat production, and growth-limiting factors. The results show that climate, growth, energy, feed, biological guidance, and memory can be linked within a single executable control cycle. Remaining limitations include the need for field validation, improved management of feed pressure, and reduction of abrupt actuator-command variations.

cs.SE↗

arXiv2026

Trans-Domain Digital Twin: Conceptual Foundations, Architecture, and Research Outlook

Complex systems comprise heterogeneous domains whose states, uncertainties, risks, and control consequences can cross domain boundaries. Existing cross-domain digital twin approaches broadly focus on comparison, reuse, semantic mapping, standardization, and interoperability, but do not inherently require operational connections among domain states, errors, objectives, constraints, decisions, and controls. This article proposes the trans-domain digital twin as an operational formulation along the continuum of Composite/Federated Digital Twin Systems. This approach connects heterogeneous domain twins through an aligned shared state, explicit coupling of data, models, states, errors, objectives, and controls, heterogeneous temporal coordination, joint decision-making, and feedback-based adaptation. The proposed framework presents a seven-layer conceptual architecture, a trans-domain orchestration core, minimum compliance conditions, a general operational formalism, progressive fast-meso-slow loops, and a single-episode offline training mechanism linked to bounded online adaptation. It also describes conceptual validation and evaluation criteria, a maturity model, a reference deployment architecture, and requirements for runtime safety, provenance, versioning, and model lifecycle management. The framework is conceptually mappable to standards for digital twins, model exchange, distributed simulation, and smart transducers; however, its formal compliance and operational effectiveness must be examined through independent benchmarks, uncertainty quantification, ablation testing, and field validation.

cs.SE↗