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Earlier sources: Energy
Energy research and engineering concern how power is produced, stored, delivered, and consumed. Follow solar and nuclear power, fusion, geothermal systems, batteries, electricity grids, and changing power demand.
SYMTRI organizes observations from public sources into a living map. Connections reflect shared subject matter; they do not establish causation or endorse a source.
Open in the map ↗725 classified signals in the fourteen-day window. Recent momentum: rising. These counts include signals awaiting readable evidence.
Earlier sources
Up to ten sources with readable evidence, ordered by their feed timestamp. These archive sources can be older than the live fourteen-day window. This list is a sample, not a measure of total activity. Dates distinguish paper publication, repository creation, model/dataset activity, Hacker News posts, and KEV catalog additions. “First archived” records when SYMTRI first stored the signal.
- OpenAlex · Published · First archived
Resilience of centralized and distributed energy systems to grid outage in winter: a district-scale assessment in Colorado, USA ↗
This study evaluates the thermal resilience of a district composed of seventeen buildings located in Colorado (USA) during a 36-hour winter power outage. The thermal performance of each building was simulated using EnergyPlus combined with MATLAB®. Three winter scenarios were investigated. The first corresponds to a baseline case where power comes from the grid. The second considers a decentralized photovoltaic (PV) system operating with and without storage. Finally, the third scenario evaluates a centralized district-level configuration based on shared PV generation, with and without storage.…
- OpenAlex · Published · First archived
Motion deblurring of long exposure images in low light condition by selective fusion of visible and near infrared images ↗
Shooting in low light condition needs prolonged exposure time to take a high quality image by increasing the amount of incident light into a camera sensor. However, long exposure images contain motion blur by object movement. Since near infrared (NIR) images are more robust to low light condition without color information than visible (VIS) images, multi-sensor fusion of VIS and NIR images provides a viable solution to low light imaging for high quality photographs. In this paper, we propose motion deblurring of long exposure images in low light condition by selective fusion of VIS and NIR ima…
- OpenAlex · Published · First archived
QoS-Aware Energy-Efficient Routing in Wireless Sensor Networks via Multi-Objective Differential Evolution ↗
Wireless Sensor Networks (WSNs) are integral to diverse applications, ranging from environmental monitoring to healthcare systems. However, inherent battery capacity constraints dictate that energy efficiency remains a paramount design criterion. Fulfilling the strict Quality of Service (QoS) demands of modern applications—such as low latency and high reliability—often conflicts with energy conservation objectives. Consequently, unequal energy dissipation among sensor nodes, particularly in the vicinity of the Base Station (BS), frequently induces the critical “energy hole” problem, thereby se…
- OpenAlex · Published · First archived
Multi-Scale Gated Aggregation for solar irradiance forecasting: A general fusion method for intra-modal and cross-modal scenarios ↗
Artificial intelligence-based solar irradiance forecasting is crucial for grid-integrated photovoltaic systems. While current methods range from textual time-series models to multimodal approaches combining text with sky images, they often grapple with high computational costs, limited feature extraction, and inefficient multimodal fusion. To address these issues, this paper proposes a novel Multi-Scale Gated Aggregation (MSGA) method—a unified, linear-complexity fusion mechanism applicable to both intra-modal (e.g., endogenous–exogenous variables) and cross-modal (e.g., text–image) scenarios.…
- OpenAlex · Published · First archived
Interface-specific evolution in directed energy deposition-processed SS316L-CuSn10-NiTi joints ↗
Abstract Directed Energy Deposition (DED) can join dissimilar alloys, but differences in thermophysical properties and interfacial chemistry make the process difficult. This work examines the interfacial microstructure and phase formation of DED-processed SS316L-CuSn10-NiTi joints, in which a CuSn10 bronze interlayer separates SS316L from NiTi. The two interfaces developed different structures. At the SS316L-CuSn10 interface, Fe and Cu redistributed and solidified in a fishbone pattern within an intermixed reaction zone of about 350 μm. The CuSn10-NiTi interface produced a narrower transition…
- OpenAlex · Published · First archived
Spectrally resolved internal heat generation and temperature prediction in multilayer photovoltaic modules under real operating conditions ↗
For a photovoltaic module operating in the field, the dynamic temperature profile through the multilayer structure is an important issue. It governs the real-time conversion efficiency of the active layer, determines its reliability, and impacts PV module service life. Yet, most thermal models describe internal heat generation through empirical equations or uniform volumetric sources, and initialize transient simulations with a uniform temperature distribution. This work develops a spectrally resolved optical-thermal model predicting the transient temperature distribution across a multilayer P…
- OpenAlex · Published · First archived
Synthetic false data injection-inspired perturbation framework for power grid attack detection using graph neural networks and deep learning models ↗
Abstract Modern power grids are exposed to False Data Injection (FDI) attacks due to their increasing dependency on digital sensing and measurement infrastructure. The adversaries deliberately manipulate sensor data for compromising control, system monitoring, and overall grid stability. Undetected attacks trigger cascading failures and severe economic disruption and bring challenges for developing a robust, data-driven detection framework for safeguarding critical energy infrastructure. The present study undertakes this challenge by introducing a structured, coordinated, feature-group-based s…
- OpenAlex · Published · First archived
Performance analysis of vertical patterned glass BIPV in zero energy buildings using explainable AI ↗
Building integrated photovoltaic (BIPV) systems offer a key alternative for urban spatial constraints, yet detailed analyses of power generation across various module concepts are still required. This study conducts an in depth analysis combining data driven approaches and explainable artificial intelligence (XAI) on a one year field dataset (20,700 observations) from 110 full sized, vertically mounted patterned glass BIPV modules. First, data analysis reveals that while voltage (Vmp) decreased with rising temperatures, current (Imp) correlated strongly with plane of array (POA) irradiance. Hi…
- OpenAlex · Published · First archived
Evaluation of free lime content in cement kilns by physics-guided support vector regression using factory energy management system ↗
The cement industry is one of the most carbon-intensive industrial sectors owing to its high energy demand. In clinker production, free lime (F-CaO) is a critical quality indicator that reflects the adequacy of heat supply during high-temperature processing; excessive F-CaO indicates insufficient thermal energy and leads to deterioration of clinker quality and energy efficiency. Accurate prediction of F-CaO is therefore important for effective quality control and energy-efficient plant operation. Previous data-driven studies have selected input variables mainly from statistical correlations, o…
- OpenAlex · Published · First archived
A novel decoupled identification-and-tracking framework for photovoltaic global maximum power point tracking under complex shading scenarios ↗
Partial shading in photovoltaic (PV) arrays introduces nonlinearities that create multiple local maxima in the power–voltage curves, often causing conventional and metaheuristic trackers to converge on suboptimal peaks. To address this, this paper proposes a novel physics-informed hierarchical framework that decouples the tracking process into two distinct stages: global identification and localized tracking. In the identification phase, a distributed Physics-Informed Neural Network (PINN) architecture estimates the maximum power point voltage of individual modules using only local electrical…
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How to assess evidence about Energy
Check each original source for its methods, release status, limitations, and supporting data. A repository announcement, a preprint, and a published study provide different kinds of evidence. SYMTRI’s subject classification helps discovery; it does not independently validate the source’s claims.
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