Proxy-Based Thermoacoustic and Energy-System Perspectives on Solar Drying Technologies: Integrating Cloud GPU Evaluation Frameworks with Advanced Thermal Storage and Control Paradigms

Abstract

The accelerating convergence of digital infrastructure and energy-intensive physical systems has generated an unprecedented need for unified evaluation frameworks capable of interpreting thermal, acoustic, and energetic performance across domains that were historically treated as separate. High-performance cloud graphics processing units used for artificial intelligence training and solar-driven food drying systems represent two extremes of this convergence: the former embodies dense computational heat generation under controlled environments, while the latter exemplifies distributed, environmentally coupled thermal processes aimed at moisture removal and food preservation. Recent proxy-based methodologies for cloud GPUs have demonstrated how indirect indicators such as thermal gradients, acoustic signatures, and airflow resistance can be leveraged to infer system efficiency and degradation without intrusive instrumentation, as articulated by Lulla, Chandra, and Sirigiri in their 2025 study on thermoacoustic proxy evaluation of cloud GPUs (Lulla et al., 2025). Parallel advances in solar drying technologies have emphasized thermal storage, phase change materials, intelligent control, and structural optimization as key levers for stabilizing temperature and reducing energy losses, as reflected across a wide body of contemporary literature (Pankaew et al., 2020; Rulazi et al., 2023; Yazici and Kose, 2024).

This article advances an original interdisciplinary argument: that proxy-based thermoacoustic evaluation frameworks developed for cloud GPUs can be theoretically and methodologically mapped onto solar drying systems to create a unified paradigm for evaluating, optimizing, and controlling thermal processes in renewable-energy-driven agro-industrial equipment. By situating solar dryers within a broader theoretical ecology of energy dissipation, interface engineering, and feedback control, the study reframes agricultural drying as a cyber-physical system whose performance can be inferred through non-invasive, proxy-driven analytics analogous to those applied in high-density computing. Drawing on polymer composite and interface science to explain material-level heat transfer and durability, as well as on thermoeconomic and control-theoretic literature to interpret system-level performance, the article constructs a comprehensive framework for understanding how heat, moisture, sound, and structure co-evolve in drying environments.

Methodologically, the research adopts a comparative theoretical design, synthesizing empirical findings from large-scale greenhouse dryers, hybrid mixed-mode systems, parabolic trough dryers, and phase change material–integrated units with the proxy-based GPU evaluation paradigm introduced by Lulla et al. (2025). Through extensive analytical triangulation, the study demonstrates that temperature stability, airflow uniformity, and acoustic emissions in solar dryers function as reliable proxies for moisture diffusion, wall heat losses, and material fatigue, much as fan noise and thermal gradients do for cloud GPUs. The results show that systems incorporating phase change materials, intelligent control algorithms, and optimized wall designs exhibit proxy signatures indicative of lower entropy production and higher exergy efficiency, consistent with thermoeconomic models reported by Nikpey et al. (2024) and Yazici and Kose (2024).

The discussion situates these findings within broader debates on sustainable energy systems, digital agriculture, and material interfaces, arguing that proxy-based evaluation not only reduces measurement costs but also enables adaptive control strategies that can be embedded into future solar dryers. By extending the logic of Lulla et al. (2025) beyond the data center and into the agricultural field, the article proposes a novel epistemology of thermal performance grounded in indirect observation, material science, and systems engineering. This approach has far-reaching implications for the design of resilient, low-carbon food processing technologies in a warming and digitizing world.