Results for “High Performance Building Systems” — Page 12

DOE OSTI2021

Integrated Models for Electrical Distribution Network Planning and District-Scale Building Energy Use

The increase of greenhouse emissions caused by a rise in global energy consumption is pushing the scientific community to develop tools that address key environmental, techno-economic and social issues. One specific area of focus is to create tools that enable the design of high-performance energy districts, including grid-interactive efficient buildings and electrical distribution infrastructure. This paper outlines the approach of integrating a synthetic distribution network tool (RNM-US) with URBANopt™, a modular and customizable software development kit for thermal and electrical modelling of buildings and energy systems at a district scale. First, we describe the algorithms implemented to integrate RNM-US with URBANopt to automatically generate the distribution network for the district considered. Following, we present a case study for the potential uses of the RNM-US integrations with URBANopt, highlighting the capabilities for economic and technical analysis of the distribution network built in relation to the electricity needs of the modelled buildings.

30 DIRECT ENERGY CONVERSION↗

DOE OSTI2025

Downscaled Earth System Model Data for Resilient Energy System Planning

The second-generation Sup3rCC dataset provides high-resolution meteorological data generated through the downscaling of multiple earth system models (ESMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6). This downscaling is performed through application of a generative machine learning approach called Super-Resolution for Renewable Resource Data (sup3r). This dataset builds on the first-generation Sup3rCC data by applying improved bias correction methods and adding downscaled precipitation to the output variables. In this presentation, we explore the output characteristics of the dataset and various validation analyses. We also present and discuss plans for the integration of this data into power system planning models using a decision-making under deep uncertainty (DMDU) methodology.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

Advancing Building Performance: Field Results of Thin-Glass Triple-Pane Window Demonstrations

To meet California and the nation's ambitious energy targets, energy use in the building sector must drop dramatically. Windows continue to be the lowest thermally performing envelope system in the nation's buildings, resulting in poor overall envelope performance and potential impacts to human health and comfort. Current best practice new window performance is typically met by double-pane low-solar-gain glazing. Thin-glass triple-pane windows are a highly promising next step forward in performance and have been deployed in two California multi-family sites to quantify field performance and building energy savings. The technology assessed offers the performance benefits of traditional triple-pane but with little increase in weight or cost, enabling incremental costs competitive with alternative energy reduction solutions for the building envelope. This paper covers a detailed investigation into the demonstration project and measured performance benefits of the windows after a full year of data collection.

Hart, Robert↗

DOE OSTI2022

It's All About the Envelope: Prioritizing Envelope Upgrades for Electrification of Cold Climate Homes

Building decarbonization via electrification on a clean grid is the most promising climate solution proposed to date for the building sector. In cold climate zones, building electrification will be driven in large part by moving from natural gas space heating to cold climate heat pumps (CCHPs). CCHPs are commercially available today, including economical cold climate air source heat pumps (ccASHPs). But there's one big problem - wide-scale adoption of ccASHPs will dramatically increase winter peak electricity demand, even with the highest efficiency ccASHP products. Furthermore, cold climate space heating loads will drive unprecedented electric system peaks during the lowest periods of renewable generation and are likely to overwhelm existing distribution systems. This scenario is avoidable by coupling electrification with building envelope upgrades to reduce peak heating loads. This paper presents a model, built from home energy audit and research data sets, that quantifies the above challenges. Results demonstrate how weatherization efforts coupled with additional high-performance envelope upgrade measures can prepare the building stock for electrification and show the benefit these measures can bring to future utility operations. Much of this envelope upgrade work is cost-effective, according to conservative cost-benefit testing and program successes to date, and is coupled with substantial non-energy benefits. However, persistent market barriers have made scaling of envelope retrofit work challenging for decades, suggesting additional policy support is required. Lessons learned from previous policy experience, combined with new technology and administrative support, create exciting potential for this decarbonization climate solution.

air sealing↗

DOE OSTI2025

Interactive Gas Chemistry for Enhanced Science Capabilities of the Energy Exascale Earth System Model Version 3

Atmospheric chemistry plays a crucial role in Earth system models (ESMs), controlling atmospheric composition and radiative balance; it is highly interactive with the physical climate, biogeochemical cycles, and human systems. However, it often imposes computational challenges in an ESM. Here we develop a full troposphere‐stratosphere interactive chemistry module for the US Department of Energy's Energy Exascale Earth System Model (E3SM). We intentionally build a streamlined module based on E3SM version 2 that interacts with other components and maintains all of major chemical and chemistry‐climate feedbacks. The module incorporates a new, highly efficient tracer advection scheme; linearization of stratospheric chemistry; and abridged tropospheric chemical mechanism with 28 reactive tracers. This new model, E3SM‐chem, can readily perform century‐long climate simulations of ozone, methane, and nitrous oxide based on emission scenarios as well as provide hourly budgets for the gas‐phase radicals that drive aerosol chemistry. We evaluate E3SM‐chem with an atmosphere‐only simulation as in the recent climate model intercomparison project (CMIP6) finding results similar to the other CMIP6 models. For the present‐day, E3SM‐chem matches the standard measurement metrics for stratospheric and tropospheric ozone, surface air quality, other key reactive gases like carbon monoxide, and the methane lifetime. Overall, E3SM‐chem maintains the climate fidelity of the baseline model while adding at most 20% to the computational cost of the atmosphere model. Hence, interactive chemistry can be a default configuration for long climate simulations at resolutions of 1° or finer, which is crucial for producing self‐consistent chemistry‐climate feedbacks that alter the climate system.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

BOPTest As a Platform for Building Controls and Grid-Interactive Buildings Workforce Training

Building automation and controls are becoming increasingly complex with the emergence of Grid Integrated Efficient Buildings (GEBs) as well as new highly efficient sequences of operation and data-driven control schemes. However, there remains a significant gap in hands-on training opportunities for building operators and technicians to gain practical experience with advanced control systems in a low-risk environment. This paper presents BOPTEST (Building Optimization Performance Test) as a suitable platform for workforce training in building controls and GEB technologies. BOPTEST provides a suite of standardized building simulation test cases with a REST API, real-time control interfaces through BACnet, semantic models connecting users to building data, and built-in calculation of control metrics and performance indicators. The platform enables trainees to interact with virtual buildings using industry-standard protocols while learning how to implement and innovate control strategies. The training platform is designed to offer a structured and interactive learning experience for building engineers, helping them effectively develop, learn, and retain skills in fault identification, troubleshooting, and correction. The workflow is divided into three main phases: 1) Setup, 2) Exercise, and 3) Review, each comprising specific activities performed by either the instructor or the student. Initial pilot training sessions have yielded positive feedback from instructors and participants and demonstrates that BOPTEST effectively fills an industry need for a low-risk training resource via simulation of real building control systems, allowing trainees to gain practical experience before working in the field. The platform's ability to provide immediate performance feedback while maintaining familiar industry interfaces makes it particularly suitable for workforce development programs. This work provides a replicable model for leveraging building simulation in control education and training.

Paul, Lazlo↗

DOE OSTI2025

BOPTEST as a Platform for Building Controls and Grid-Interactive Buildings Workforce Training

Building automation and controls are becoming increasingly complex with the emergence of Grid Integrated Efficient Buildings (GEBs) as well as new highly efficient sequences of operation and data-driven control schemes. However, there remains a significant gap in hands-on training opportunities for building operators and technicians to gain practical experience with advanced control systems in a low-risk environment. This paper presents BOPTEST (Building Optimization Performance Test) as a suitable platform for workforce training in building controls and GEB technologies. BOPTEST provides a suite of standardized building simulation test cases with a REST API, real-time control interfaces through BACnet, semantic models connecting users to building data, and built-in calculation of control metrics and performance indicators. The platform enables trainees to interact with virtual buildings using industry-standard protocols while learning how to implement and innovate control strategies. The training platform is designed to offer a structured and interactive learning experience for building engineers, helping them effectively develop, learn, and retain skills in fault identification, troubleshooting, and correction. The workflow is divided into three main phases: 1) Setup, 2) Exercise, and 3) Review, each comprising specific activities performed by either the instructor or the student. Initial pilot training sessions have yielded positive feedback from instructors and participants and demonstrates that BOPTEST effectively fills an industry need for a low-risk training resource via simulation of real building control systems, allowing trainees to gain practical experience before working in the field. The platform's ability to provide immediate performance feedback while maintaining familiar industry interfaces makes it particularly suitable for workforce development programs. This work provides a replicable model for leveraging building simulation in control education and training.

Paul, Lazlo↗

DOE OSTI2021

Advancing Construction through the Buildings Workforce: Preprint

Buildings are America's energy hogs, consuming over 70 percent of all electricity and over 50 percent of all natural gas produced across the country. Achieving a clean energy future requires us to reinvent how buildings manage energy resources and how consumers demand it. The U.S. Department of Energy is investing in a range of technological advancements that are paving the way to a future where buildings are no longer simply energy consumers, but rather are part of an integrated system that help manage energy resources in a way that supports the electricity grid. This paradigm shift presents an opportunity to increase the efficiency of the built environment, but will only be realized if we build a knowledgeable workforce to design, construct, and operate these high-performance buildings in step with the rate of technological advancement.

ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION↗

DOE OSTI2022

Semi-Annual Report for Modular Integrated Gas High Temperature Reactor Development during Performance Period April 2022 - September 2022

Horizontal Compact High Temperature Gas Reactor (HC-HTGR) is being designed by a multidisciplinary team of nuclear, mechanical, and structural engineers under the support of a DOE-NE Advanced Reactor Demonstration Program’s Advanced Reactor Concepts-20 (ARC-20) award. The objective of this ARC-20 project is to deliver a conceptual design for the proposed HC-HTGR in 3 years and support its commercialization as a safe, low-cost HTGR. Argonne National Laboratory (Argonne) is responsible for the design and analysis of the reactor cavity cooling system (RCCS) as a safety system for passive decay heat removal of the reactor concept. Additionally, Argonne is providing analysis of the primary coolant system to ensure temperatures within the core remain below safety margins during steady-state and potential accident scenarios. This second semi-annual report summarized the progress made at Argonne on the two tasks during the second half of FY22. As a part of the RCCS design task, a scoping calculation in estimating HVAC capability for the HC-HTGR reactor building was performed. A water panel modeling study was first performed with the test case, which confirms the capability of the RELAP5-3D modeling approach to explore various design options of the HC-HTGR RCCS under consideration. Then, a reference RELAP5-3D model for the unit geometry of the preliminary design of the HC-HTGR RCCS was developed. A preliminary performance analysis was conducted to evaluate the performances of a single-phase natural circulation and panel conduction in various operating conditions. For the primary coolant system analysis task, preliminary thermal hydraulic analysis of the HC-HTGR core design was performed with a high resolution 1D fluid-3D solid coupled model using the System Analysis Module (SAM) to assess the assembly coolant channel and bypass flow mass flow rate distribution. Some preliminary work on the development of a full core reduced order model was discussed following the assembly level model to predict the core wide coolant flow distribution and to model certain operational and accidental transients.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2025

Expanding on the BRIAR Dataset: A Comprehensive Whole Body Biometric Recognition Resource at Extreme Distances and Real-World Scenarios (Collections 1-4)

The state-of-the-art in biometric recognition algorithms and operational systems has advanced quickly in recent years providing high accuracy and robustness in more challenging collection environments and consumer applications. However, the technology still suffers greatly when applied to non-conventional settings such as those seen when performing identification at extreme distances or from elevated cameras on buildings or mounted to UAVs. This paper summarizes an extension to the largest dataset currently focused on addressing these operational challenges, and describes its composition as well as methodologies of collection, curation, and annotation.

Cornett, David [ORNL] (ORCID:0000000222910860)↗

DOE OSTI2020

Semantic Interoperability to Enable Smart, Grid-Interactive Efficient Buildings

Achieving a widespread transition to grid-interactive, efficient buildings (GEBs) depends critically on there being sufficient interoperability among connected building systems. While many critical elements already exist at the technical interoperability level (TCP/IP, BACnet, etc.), a lack of interoperability in the semantic level hinders streamlined integration of interdependent applications. Semantics refers to expressing information about “things” in a way that can be consistently understood by applications. Key components of formalized semantics include identifying what a “thing” is (its “type”), defining general information about that “thing” (its characteristics or properties), and defining the appropriate relationships of that “thing” to other “things” (its function or role in a larger system). Although this might seem initially trivial, the success of smart building applications is highly dependent on maintaining consistent self-descriptive notions of the “things”. Without semantic interoperability, it is technically difficult, labor-intensive, and cost-prohibitive to enable three key objectives of GEBs: optimizing performance, automatically identifying and diagnosing faults, and delivering grid services. Industry, academia, and standards bodies have invested effort in developing information models to facilitate semantic interoperability, however, they have not been widely adopted across the U.S. commercial building portfolio. This paper will present a pathway to drive semantic interoperability through a three-pronged approach to be led by the DOE Building Technologies Office in partnership with NIST and multiple national laboratories comprising: 1) industry engagement and coordination across existing efforts; 2) a semantic interoperability standard that empowers building owners to identify and require interoperable attributes when procuring equipment and applications; 3) tools to assist in implementation and a test framework to verify compliance of products with semantic interoperability specifications. This approach is designed to accelerate the timeline for adoption of semantic interoperability specifications. The intent is to reduce soft costs associated with implementing advanced controls, fault detection and diagnostics, and other smart building technologies and use cases as a necessary step in achieving an energy efficient smart grid future.

Bergmann, Harry↗

DOE OSTI2020

Semantic Interoperability to Enable Smart, Grid-Interactive Efficient Buildings

Achieving a widespread transition to grid-interactive, efficient buildings (GEBs) depends critically on there being sufficient interoperability among connected building systems. While many critical elements already exist at the technical interoperability level (TCP/IP, BACnet, etc.), a lack of interoperability in the semantic level hinders streamlined integration of interdependent applications. Semantics refers to expressing information about “things” in a way that can be consistently understood by applications. Key components of formalized semantics include identifying what a “thing” is (its “type”), defining general information about that “thing” (its characteristics or properties), and defining the appropriate relationships of that “thing” to other “things” (its function or role in a larger system). Although this might seem initially trivial, the success of smart building applications is highly dependent on maintaining consistent self-descriptive notions of the “things”. Without semantic interoperability, it is technically difficult, labor-intensive, and cost-prohibitive to enable three key objectives of GEBs: optimizing performance, automatically identifying and diagnosing faults, and delivering grid services. Industry, academia, and standards bodies have invested effort in developing information models to facilitate semantic interoperability, however, they have not been widely adopted across the U.S. commercial building portfolio. This paper will present a pathway to drive semantic interoperability through a three-pronged approach to be led by the DOE Building Technologies Office in partnership with NIST and multiple national laboratories comprising: 1) industry engagement and coordination across existing efforts; 2) a semantic interoperability standard that empowers building owners to identify and require interoperable attributes when procuring equipment and applications; 3) tools to assist in implementation and a test framework to verify compliance of products with semantic interoperability specifications. This approach is designed to accelerate the timeline for adoption of semantic interoperability specifications. The intent is to reduce soft costs associated with implementing advanced controls, fault detection and diagnostics, and other smart building technologies and use cases as a necessary step in achieving an energy efficient smart grid future.

30 DIRECT ENERGY CONVERSION↗

DOE OSTI2020

BEEAM (Building Electrical Efficiency Analysis Model) [SWR-20-107]

Modern high-performance buildings exhibit an increasing number of building loads that use direct current (DC) electricity internally, rather than alternating current (AC), due to the advent of low-cost computing and advanced power electronics. Powering DC devices from the AC grid requires AC/DC power conversion, which introduces energy losses and reduces efficiency. As DC loads proliferate, the cumulative wasted energy associated with hundreds of millions of AC/DC converters has become one of the broadest energy savings opportunities in buildings. DC power distribution systems have been proposed as an elegant and transformative solution to the problem of DC devices. In a DC distribution system, the building's wires carry DC electricity, rather than AC; and a few centralized, highly efficient AC/DC converters replace the many smaller, less efficient converters that serve individual DC loads. Unfortunately, the trade-offs associated with DC distribution systems are not well understood. Reported energy savings associated with DC power distribution differ widely and have not been well validated. The Building Electrical Efficiency Analysis Model (BEEAM) is a Modelica library that simulates the efficiency of building electrical distribution systems using harmonic power flow. BEEAM can model a wide variety of building distribution topologies, including three-phase AC, single-phase AC, unipolar DC, bipolar DC, and hybrid networks under both balanced and unbalanced load conditions. BEEAM accurately models power electronic converter losses, provides granular estimates of losses throughout the distribution system, and properly models efficiency at part load conditions. Users can package BEEAM within a functional mockup unit (FMU), enabling co-simulation with other modeling platform, such as EnergyPlus. In summary, BEEAM provides a tool suite for fair and accurate comparison of the efficiency of building electrical distribution systems, including AC, DC, and hybrid systems.

Frank, Stephen↗

DOE OSTI2023

Integrated End-to-end Performance Prediction and Diagnosis for Extreme Scientific Workflows

This report details recent progress for the ASCR funded project “Integrated End-to-end Performance Prediction and Diagnosis for Extreme Scientific Workflows”. We refer to the project as IPPD/2, reflecting the 2017 renewal under expanded scope and partners In IPPD/2, we increased our research scope to include data motion. We are focusing on three major aspects: a) observe how data is generated, distributed, and used; b) analyze how data is (repeatedly) consumed with a focus both on repeated patterns and anomalies; and c) explore how to optimize data motion. This new work on data motion will augment and complement IPPD/2’s research that focused on the computational aspects of tasks. We leverage and extend our existing tools and demonstrate our work on the Belle II workflow suite as well as on workflows from NSLS-II. The highlights of our work are as follows: Provenance for Workflows: Provenance is used to provide information enabling quality control, re-run computational workflows, and reproduce results. IPPD/2 has been building a scalable provenance management system that enables the capture of provenance from the high-level workflow through all relevant system levels in one integrated environment. Leveraging this work, our recent efforts have included using provenance as an enabling technique. Workload characterization: Leveraging provenance and analysis, we characterize data movement within network, storage, and memory over a variety of workloads. This characterization enables an understanding by performance analysts and application developers of the range of behaviors that could be expected. Performance Prediction for Workflows: The goal of modeling distributed workflows is to understand performance bottlenecks and enable more intelligent task scheduling to optimize selected metrics of interest (e.g., task throughput or output data rate). IPPD/2 has utilized both analytical and AI/ML modeling methodologies for performance modeling. Advanced Scheduling and Fault Modeling for Workflows: Scheduling of large-scale scientific workflows on geographically distributed resources is a challenging problem. To improve workflow throughput, we combined novel scheduling algorithms with task predictions from performance modeling and fault modeling. Dynamically Alleviating Bottlenecks in Workflows: Exploiting our provenance, analysis, and modeling efforts, we have explored and developed several techniques for dynamically detecting and alleviating bottlenecks in data movement. In particular, we have spent considerable effort demonstrating our techniques on production-like workflow configurations.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Development of a medium-duty stoichiometric diesel micro-pilot natural gas engine

Fueling a compression-ignition engine with premixed natural gas offers the potential to combine a clean-burning, low-carbon fuel with a high compression ratio, high-efficiency engine. This work describes the development of a multi-cylinder 6.7 L diesel engine converted to run stoichiometric diesel micro-pilot/ natural gas premix combustion with a maximum diesel contribution target of 5% of the total fuel energy and a three-way catalyst aftertreatment system. Results are given by comparing the stoichiometric combustion to the diesel baseline operation, showing combustion characteristics differences, including the rapid two stage heat release. A high load output of 23 bar brake mean effective pressure was obtained with diesel-like brake thermal efficiency of 41%. This operating condition enabled a brake specific CO 2 emissions reduction of up to 25% when compared to diesel. It was observed that the low load output is limited by combustion stability when operated at stoichiometric condition. The three-way catalyst is observed to run at peak efficiency with an equivalence ratio of 1.01. Injector fouling was observed through the inspection of the nozzle and its internal parts, indicating carbon build-up similar to that seen in injector coking mechanisms. A comparison of the developed engine to other engine technologies is given, showing that the diesel micro-pilot natural gas engine performance is in good standing among other diesel and gas engines in the market.

Engineering↗

DOE OSTI2022

Multi phenomena melt pool sensor data fusion for enhanced process monitoring of laser powder bed fusion additive manufacturing

Finding actionable trends in laser-based metal additive manufacturing process monitoring data is challenging owing to the diversity and complexity of the underlying physical interactions. A single monitoring solution that captures a particular process phenomenon, such as a photodiode that tracks melt pool intensity, is not alone capable of evaluating process stability or detecting flaw formation with sufficient precision for routine application in industry. In this work, to improve flaw detection performance, we adopted a data fusion approach that captures multiple process phenomena. To demonstrate this, we acquired data from laser powder bed fusion (LPBF) builds of cylindrical specimens produced with different laser spot sizes, emulating defocusing due to process faults such as thermal lensing. The resulting specimens had porosity of varying types and severity, quantified by post-build non-destructive X-ray computed tomography, Archimedes density measurements, and destructive metallographic characterization. During the build, the melt pool state was monitored with two coaxial high-speed video cameras and a temperature field imaging system. Physically intuitive low-level melt pool signatures, such as melt pool temperature, shape and size, and spatter intensity were extracted from this high-dimensional, image-based sensor data. These process signatures were subsequently used as input features in relatively simple machine learning models, such as a support vector machine, which were trained to detect laser defocusing, and in addition, predict porosity type and severity. The results show that the data fusion approach significantly enhanced system performance by reducing the overall false positive rate from ~ 0.1 to ~ 0.001 without sacrificing the true positive rate (~0.90). These results were at par with a black-box, deep machine learning approach (convolutional neural network).

36 MATERIALS SCIENCE↗

DOE OSTI2022

Cross-Laminated Timber Workshop: Pathways and Priorities for Cross-Laminated Timber Building Systems

A virtual workshop titled "BTO Cross-Laminated Timber Workshop: Pathways and Priorities for CLT Building Systems," was held on April 19, 2021, to identify research and development pathways, including the embodied energy content, operational energy efficiency, wall moisture profiles, structural connector durability, and health monitoring systems for CLT wall systems. In the workshop, perspectives were gathered from a wide range of stakeholders across North America from academia, the mass timber industry, trade groups, and federal government departments. The participants had knowledge in one or more areas of CLT building performance, production and construction, supply and demand dynamics of CLT panels, building codes, and recycling of CLT panels. To capture potential research opportunities from the participants in the mass timber field, the workshop was structured with the following objectives: 1. Identify the research and development opportunities to overcome technology gaps, integration issues, and market adoption challenges that are currently preventing the greater deployment of CLT, and 2. Understand what priorities and pathways are needed to advance energy efficient, high- rise CLT building systems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2022

Assessment of Low-Cost Minisplit Heat Pump Connection System

This project was funded by SCE's Emerging Technologies Program, and evaluates the feasibility of a connection system that can pave the path to accelerated, cost-effective adoption of high-efficiency Minisplit Heat Pump (MSHP) systems. This report details the characterization of this connection system and a heat pump enabled with this technology in a laboratory setting, and assesses the energy and cost impact applicable to residential buildings in SCE service territory. The energy and economic analysis leverages NREL's ResStock TM modeling approach based on the EnergyPlus ® hourly simulation platform. The connection system can be incorporated into existing MSHP architectures. This reduces installation time from 10 to 20 man hours to approximately one hour or less, dramatically lowering total installation costs without adversely impacting heat pump performance. This report characterizes the connection system's leakage performance while connected and disconnected, as well as leakage over several connection/disconnection cycles, commensurate with manufacturer specifications for the individual components. The connector was incorporated into an off-the-shelf MSHP. Performance was compared to an identical unmodified heat pump. The connector had no impact on performance. Large-scale hourly energy simulations were performed for 22,574 homes across 15 counties in SCE service territory. The analysis was performed using baseline assumptions about the penetrations of window air conditioners (~18%) and six upgrade scenarios for these air conditioners. All scenarios assumed 100% adoption of the Connector-Supported Heat Pump (CSHP) in place of window air conditioners: MSHPs at Seasonal Energy Efficiency Ratio (SEER) 17, 25, and 33, and CSHPs at SEER 17, 25, and 33. Results show the increased adoption of high-efficiency heat pumps can result in up to 29% air conditioning energy savings for homes with window air conditioners.

42 ENGINEERING↗