THE INTERNET IS THINKING
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 ↗698 classified signals in the fourteen-day window. Recent momentum: steady. 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
Numerical analysis of the fluid flow and heat exchange characteristics in a low-temperature and high-permeability reservoir of a heat storage and heating system ↗
It is a promising energy strategy to utilize a shallow, low-temperature geothermal reservoir for seasonal heat storage and heating, with the potential to meet winter heating needs in decentralized rural buildings. The fluid flow and heat exchange in the reservoir govern the thermal performance of this heat storage and heating mode. However, for a U-shaped closed-loop geothermal system with long-term cyclic operation, the characteristics of fluid flow and heat exchange in a low-temperature and highly permeable water-saturated reservoir lacking background groundwater flow remain poorly understoo…
- OpenAlex · Published · First archived
DSFormer: An Enhanced Dual-Selective Fusion Transformer Framework for Hyperspectral Image Classification++ ↗
Hyperspectral image classification requires joint modeling of spectral signatures and spatial structure. In patch-based classification, each input patch is assigned the label of its center pixel, although neighboring pixels may belong to different land-cover classes. This setting motivates coordinating shallow spatial features, contextual refinement within the patch, and supervision of the resulting representation. We propose DSFormer++, an enhanced framework based on the original Dual Selective Fusion Transformer Network (DSFormer). Shallow Feature Compensation (SFC) combines shallow and patc…
- OpenAlex · Published · First archived
LSR: Eliminating Loop Control Overhead for Energy-Efficient Processors ↗
Loops constitute a small fraction of static code but dominate dynamic execution time and control overhead, posing significant challenges for energy-efficient mobile and embedded processors. This paper introduces Loop Semantic Recognition (LSR) , a microarchitectural technique that dynamically infers loop semantics to eliminate loop control overhead without requiring compiler support or ISA extensions. We further propose three complementary optimizations: Branch Strength Reduction (BSR), Hardware Loop Unrolling (HLU), and Stride Value Prediction (SVP), which progressively remove redundant contr…
- OpenAlex · Published · First archived
Development and implementation of a surrogate model for bare critical Mass estimation in nuclear fuel cycle simulator ↗
In this study, estimation functions of bare critical mass (BCM) and heat content (HC) of nuclear materials were developed and introduced into a nuclear fuel cycle simulator, the Nuclear Material Balance (NMB), in order to use them for non-proliferation studies of future advanced nuclear fuel cycles. HC is defined as the total decay heat of one BCM of material. To reduce the calculation cost of Monte Carlo calculation for BCM, a surrogate model was developed. Several regression models were compared using BCM data calculated by MCNP-6.2 and JENDL-5 for randomly generated actinide compositions, a…
- OpenAlex · Published · First archived
Multi-camera in-situ monitoring for emissivity-corrected temperature measurement in laser beam directed energy deposition ↗
Abstract Temperature measurement is essential in metal additive manufacturing, as the spatio-thermal profile strongly influences the microstructure and therefore the key mechanical properties of the produced components. Conventional infrared thermography is widely used for in-situ temperature monitoring. However, its quantitative interpretation is often limited by the varying and generally unknown emissivity of the metal surfaces throughout the build process. This paper presents a pipeline that combines visual and infrared imaging to obtain more physically consistent temperature fields under s…
- OpenAlex · Published · First archived
Intelligent Systems for Space Conditioning and Shading in Buildings: A Systematic Review of Artificial Intelligence Techniques and Their Energy Impact ↗
Artificial intelligence (AI) is increasingly applied to heating, ventilation, and air-conditioning (HVAC) control, whereas solar-radiation management still relies mainly on reactive strategies; whether AI capabilities validated in HVAC could be transferred to solar control has not been systematically assessed. This review compares both domains in terms of experimental maturity, climatic coverage, and input variables. Web of Science studies (2015–2026) reporting quantitative energy-demand variations were systematically reviewed following PRISMA 2020 and synthesized descriptively, with a sensiti…
- OpenAlex · Published · First archived
Sequence-Conditioned Physics-Informed Neural Network for Lithium-Ion Battery State of Health Estimation Using Charging Segments at High State of Charge ↗
Accurate and reliable state of health (SOH) estimation is essential for lithium-ion battery safety and lifetime management. Physics-informed neural networks (PINNs) integrate battery degradation knowledge with deep learning to improve the physical consistency of SOH estimation. However, existing PINNs insufficiently capture degradation evolution across consecutive cycles and show limited applicability across battery chemistries and charge/discharge protocols. To address these issues, we propose a sequence-conditioned physics-informed neural network (SC-PINN) that uses a gated recurrent unit (G…
- OpenAlex · Published · First archived
Narrowband Internet of Things over Non-Terrestrial Networks for Remote Renewable-Energy Management: Architecture and Performance Evaluation ↗
Reliable communication is essential for monitoring and supervisory operation of renewable-energy facilities beyond terrestrial-network coverage. This study proposes a four-layer Internet of Things (IoT) architecture aligned with 3GPP Release 17, integrating sensors, an edge gateway, Narrowband IoT (NB-IoT) access through a transparent satellite payload, terrestrial core-network functions, and centralized IoT, Energy Management System (EMS), and Supervisory Control and Data Acquisition (SCADA) applications. A 3GPP-aligned analytical framework evaluates satellite geometry, transparent-path propa…
- OpenAlex · Published · First archived
A thermally integrated Carnot battery incorporating a novel dual-pressure evaporation cycle for deep utilization of waste heat: Parameter analysis and working-fluid optimization ↗
The majority of contemporary thermally integrated Carnot batteries have inadequate waste heat use during the discharging process. Leveraging the integrated heat exchange capability of the multi-stream heat exchanger, this study proposes a thermally integrated Carnot battery incorporating a new dual-pressure evaporation cycle (DPE-CB). In order to achieve deep coupling and effective recovery of waste heat energy, this system uses a dual-pressure cascade heat addition mode during the discharging process, where the low-pressure stage absorbs heat first, followed by preheating in the high-pressure…
- OpenAlex · Published · First archived
FlexENN: A Graph Neural Network for Binding Energy Prediction of Globular and Intrinsically Disordered Proteins ↗
Abstract Intrinsically disordered proteins (IDPs) drive a large fraction of cellular signaling, transcription, and assembly through interfaces that often lack a defined geometry, making the prediction of their binding energies challenging for methods developed primarily for folded complexes. Here, we introduce FlexENN, an interface-focused message-passing graph neural network framework comprising two independently trained models: FlexENN-F for folded protein complexes and FlexENN-I for complexes containing a disordered partner. The FlexENN architecture constructs a local interface graph in whi…
Live window recorded . This is the ingestion observation time, not the publication or discovery date of each source.
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.
See the collection and counting methodology ↗ · Read the weekly synthesis ↗
Follow a thread
Explore related regions
These navigation suggestions are part of the map’s editorial structure, rather than measured evidence of a connection.