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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Toward a subhourly net zero energy district design through integrated building and distribution system modeling

A modeling framework integrating both building energy modeling and power system modeling is introduced for the design of net zero energy (NZE) districts for the simultaneous selection of both demand-side efficiency measures and supply-side generation technologies. A novel district control scheme is proposed for pursuing NZE on a subhourly basis while mitigating potential grid impacts such as power backfeeding and voltage violations. As a case study, Pena Station NEXT, a new 100-building, mixed-use district on a 1200-node distribution feeder in Denver, Colorado, is modeled in the integrated framework. An exhaustive scenario analysis is conducted for sizing the district's distributed energy resources, considering multiple objectives such as capital cost, net energy import, and equipment violations. Here, when trying to achieve annual NZE, the district incurs frequent operating violations, and achieving NZE on a 15-min basis is also limited by seasonal fluctuations in photovoltaic output, illustrating the need for diverse generation or seasonal storage. As a practical compromise, both annual and 15-min district import can be reduced by ~78% without significant violations.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Quantitative analysis of cost savings and occupants’ preferences in grid-interactive smart home operation

Many utility companies in the United States have introduced time-of-use (TOU) rates for homeowners with the goal of regulating electricity consumption during peak hours. The electrical appliances in homes include various thermostatically controlled devices, such as air conditioners (AC) for thermal comfort, and nonthermostatically controlled devices such as clothes washers. As a result, homeowners face the complicated challenge of economically operating multiple electrical appliances in their homes while maintaining comfort and convenience. This is usually due to the lack of an explicit understanding of the correlation between cost saving and the users’ comfort. To understand the correlation, this article is designed to construct a framework by integrating three major components: a multi-objective optimization method accommodating multiple competing goals with different weights, a learning-based system modeling approach describing the dynamics and thermal coupling effects of appliances, and a novel comfort index method differentiating preferred and acceptable thermal comfort. Our proposed framework can allow the indoor air temperature to fall into the "preferred" range with a marginal cost increase. Furthermore, the simulation result shows that an additional 8 h for the preferred thermal comfort can be achieved with a cost increase of only 1.77%.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2016

Simulation of Mission Phases

This position with the Simulation and Graphics Branch (ER7) at Johnson Space Center (JSC) provided an introduction to vehicle hardware, mission planning, and simulation design. ER7 supports engineering analysis and flight crew training by providing high-fidelity, real-time graphical simulations in the Systems Engineering Simulator (SES) lab. The primary project assigned by NASA mentor and SES lab manager, Meghan Daley, was to develop a graphical simulation of the rendezvous, proximity operations, and docking (RPOD) phases of flight. The simulation is to include a generic crew/cargo transportation vehicle and a target object in low-Earth orbit (LEO). Various capsule, winged, and lifting body vehicles as well as historical RPOD methods were evaluated during the project analysis phase. JSC core mission to support the International Space Station (ISS), Commercial Crew Program (CCP), and Human Space Flight (HSF) influenced the project specifications. The simulation is characterized as a 30 meter +V Bar and/or -R Bar approach to the target object's docking station. The ISS was selected as the target object and the international Low Impact Docking System (iLIDS) was selected as the docking mechanism. The location of the target object's docking station corresponds with the RPOD methods identified. The simulation design focuses on Guidance, Navigation, and Control (GNC) system architecture models with station keeping and telemetry data processing capabilities. The optical and inertial sensors, reaction control system thrusters, and the docking mechanism selected were based on CCP vehicle manufacturer's current and proposed technologies. A significant amount of independent study and tutorial completion was required for this project. Multiple primary source materials were accessed using the NASA Technical Report Server (NTRS) and reference textbooks were borrowed from the JSC Main Library and International Space Station Library. The Trick Simulation Environment and User Training Materials version 2013.0 release was used to complete the Trick tutorial. Multiple network privilege and repository permission requests were required in order to access previous simulation models. The project was also an introduction to computer programming and the Linux operating system. Basic C++ and Python syntax was used during the completion of the Trick tutorial. Trick's engineering analysis and Monte Carlo simulation capabilities were observed and basic space mission planning procedures were applied in the conceptual design phase. Multiple professional development opportunities were completed in addition to project duties during this internship through the System for Administration, Training, and Education Resources for NASA (SATERN). Topics include: JSC Risk Management Workshop, CCP Risk Management, Basic Radiation Safety Training, X-Ray Radiation Safety, Basic Laser Safety, JSC Export Control, ISS RISE Ambassador, Basic SharePoint 2013, Space Nutrition and Biochemistry, and JSC Personal Protective Equipment. Additionally, this internship afforded the opportunity for formal project presentation and public speaking practice. This was my first experience at a NASA center. After completing this internship I have a much clearer understanding of certain aspects of the agency's processes and procedures, as well as a deeper appreciation from spaceflight simulation design and testing. I will continue to improve my technical skills so that I may have another opportunity to return to NASA and Johnson Space Center.

Carlstrom, Nicholas Mercury↗
NASA NTRS2021

Predicting Arrival and Departure Runway Assignments with Machine Learning

Runway assignments at major airports are made by air traffic controllers subject to various constraints, and to achieve various objectives. In this research, we describe our efforts training machine learning (ML) models to predict both departure and arrival runway assignments using an entirely data-driven approach. This approach is compared to existing rule-based approaches developed in previous research using input from Subject Matter Experts. The models have features derived from various FAA data feeds, and leverage multiple machine learning algorithms. Results for models trained for nine major U.S. airports are described and compared to one another across various important dimensions. Particular attention was paid to developing a repeatable framework for training these models so the approach could be scaled to other airports, and to developing models that are useful in a real-time environment. In addition, the models were designed to be functional in a real-time environment to support NASA’s ATD-2 project, as part of an ML-powered shadow system to compare against the performance of the fielded system.

machine learning↗
NASA NTRS2021

Predicting Arrival and Departure Runway Assignments with Machine Learning

Runway assignments at major airports are made by air traffic controllers subject to various constraints, and to achieve various objectives. In this research, we describe our efforts training machine learning (ML) models to predict both departure and arrival runway assignments using an entirely data-driven approach. This approach is compared to existing rule-based approaches developed in previous research using input from Subject Matter Experts. The models have features derived from various FAA data feeds, and leverage multiple machine learning algorithms. Results for models trained for nine major U.S. airports are described and compared to one another across various important dimensions. Particular attention was paid to developing a repeatable framework for training these models so the approach could be scaled to other airports, and to developing models that are useful in a real-time environment. In addition, the models were designed to be functional in a real-time environment to support NASA’s ATD-2 project, as part of an ML-powered shadow system to compare against the performance of the fielded system.

machine learning↗
NASA NTRS2012

A Thermodynamically-Based Mesh Objective Work Potential Theory for Predicting Intralaminar Progressive Damage and Failure in Fiber-Reinforced Laminates

A thermodynamically-based work potential theory for modeling progressive damage and failure in fiber-reinforced laminates is presented. The current, multiple-internal state variable (ISV) formulation, enhanced Schapery theory (EST), utilizes separate ISVs for modeling the effects of damage and failure. Damage is considered to be the effect of any structural changes in a material that manifest as pre-peak non-linearity in the stress versus strain response. Conversely, failure is taken to be the effect of the evolution of any mechanisms that results in post-peak strain softening. It is assumed that matrix microdamage is the dominant damage mechanism in continuous fiber-reinforced polymer matrix laminates, and its evolution is controlled with a single ISV. Three additional ISVs are introduced to account for failure due to mode I transverse cracking, mode II transverse cracking, and mode I axial failure. Typically, failure evolution (i.e., post-peak strain softening) results in pathologically mesh dependent solutions within a finite element method (FEM) setting. Therefore, consistent character element lengths are introduced into the formulation of the evolution of the three failure ISVs. Using the stationarity of the total work potential with respect to each ISV, a set of thermodynamically consistent evolution equations for the ISVs is derived. The theory is implemented into commercial FEM software. Objectivity of total energy dissipated during the failure process, with regards to refinements in the FEM mesh, is demonstrated. The model is also verified against experimental results from two laminated, T800/3900-2 panels containing a central notch and different fiber-orientation stacking sequences. Global load versus displacement, global load versus local strain gage data, and macroscopic failure paths obtained from the models are compared to the experiments.

Pineda, Evan J.↗
DOE OSTI2023

Understanding Dynamics and Thermodynamics of ENSO and Its Complexity Simulated by E3SM and Other Climate Models

Despite the seeming success of most state-of-the-art climate models in simulating the El Niño-Southern Oscillation (ENSO), there is strong evidence that models achieve realistic levels of ENSO activity do so often for wrong reasons. This is owing to an often occurred near cancelation of large errors in terms of contributions to ENSO growth rate from coupled dynamic and thermodynamic feedback processes. Climate models remain deficient in simulating the observed ENSO’s spatial and temporal complexity that involves interplays of coupled dynamic and thermodynamic feedbacks, interactions across multiple scales, nonlinear processes in the tropical atmosphere and ocean system, biases in mean sate and physical processes, and influences external to equatorial Pacific coupled ENSO dynamics. Our proposed research aims at advancing predictive and process-level understandings of ENSO simulated in E3SM and other climate models under current and future climate conditions with two main objectives: (i) better understanding the aforementioned broad range interactive processes and sources that control fundamental properties of ENSO in E3SM and CIMP6 outputs as well as in observational (reanalysis) data sets, using a hierarchical of coupled dynamical frameworks consisting of theoretical analysis, intermediate complexity modeling, and coupled dynamic diagnostics; (ii) to use this understanding to explore pathways towards improving E3SM’s capability of simulating ENSO and its complexity. More specifically, we will focus on four main thrusts of research: (1) ENSO’s dynamic and thermodynamic feedbacks; (2) the across-scale interactions of ENSO with annual cycle and MJO/WWB/TIW (Madden Julian Oscillation/Westerly Wind Burst/Tropical Instability Wave) activity; (3) key nonlinear processes of ENSO involving atmospheric convective thresholds, nonlinear ocean dynamic heating, and thermocline outcropping; and (4) the impacts of climate mean-state biases/changes and perturbed physical processes on simulated ENSO and its complexity.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1990

Autonomous power expert system

The goal of the Autonomous Power System (APS) program is to develop and apply intelligent problem solving and control technologies to the Space Station Freedom Electrical Power Systems (SSF/EPS). The objectives of the program are to establish artificial intelligence/expert system technology paths, to create knowledge based tools with advanced human-operator interfaces, and to integrate and interface knowledge-based and conventional control schemes. This program is being developed at the NASA-Lewis. The APS Brassboard represents a subset of a 20 KHz Space Station Power Management And Distribution (PMAD) testbed. A distributed control scheme is used to manage multiple levels of computers and switchgear. The brassboard is comprised of a set of intelligent switchgear used to effectively switch power from the sources to the loads. The Autonomous Power Expert System (APEX) portion of the APS program integrates a knowledge based fault diagnostic system, a power resource scheduler, and an interface to the APS Brassboard. The system includes knowledge bases for system diagnostics, fault detection and isolation, and recommended actions. The scheduler autonomously assigns start times to the attached loads based on temporal and power constraints. The scheduler is able to work in a near real time environment for both scheduling and dynamic replanning.

Ringer, Mark J.↗
NASA NTRS1990

Autonomous power expert system

The goal of the Autonomous Power System (APS) program is to develop and apply intelligent problem solving and control technologies to the Space Station Freedom Electrical Power Systems (SSF/EPS). The objectives of the program are to establish artificial intelligence/expert system technology paths, to create knowledge based tools with advanced human-operator interfaces, and to integrate and interface knowledge-based and conventional control schemes. This program is being developed at the NASA-Lewis. The APS Brassboard represents a subset of a 20 KHz Space Station Power Management And Distribution (PMAD) testbed. A distributed control scheme is used to manage multiple levels of computers and switchgear. The brassboard is comprised of a set of intelligent switchgear used to effectively switch power from the sources to the loads. The Autonomous Power Expert System (APEX) portion of the APS program integrates a knowledge based fault diagnostic system, a power resource scheduler, and an interface to the APS Brassboard. The system includes knowledge bases for system diagnostics, fault detection and isolation, and recommended actions. The scheduler autonomously assigns start times to the attached loads based on temporal and power constraints. The scheduler is able to work in a near real time environment for both scheduling an dynamic replanning.

Ringer, Mark J.↗
NASA NTRS2009

Low Impact Docking System (LIDS)

Since 1996, NASA has been developing a docking system that will simplify operations and reduce risks associated with mating spacecraft. This effort has focused on developing and testing an original, reconfigurable, active, closed-loop, force-feedback controlled docking system using modern technologies. The primary objective of this effort has been to design a docking interface that is tunable to the unique performance requirements for all types of mating operations (i.e. docking and berthing, autonomous and piloted rendezvous, and in-space assembly of vehicles, modules and structures). The docking system must also support the transfer of crew, cargo, power, fluid, and data. As a result of the past 10 years of docking system advancement, the Low Impact Docking System or LIDS was developed. The current LIDS design incorporates the lessons learned and development experiences from both previous and existing docking systems. LIDS feasibility was established through multiple iterations of prototype hardware development and testing. Benefits of LIDS include safe, low impact mating operations, more effective and flexible mission implementation with an anytime/anywhere mating capability, system level redundancy, and a more affordable and sustainable mission architecture with reduced mission and life cycle costs. In 1996 the LIDS project, then known as the Advanced Docking Berthing System (ADBS) project, launched a four year developmental period. At the end of the four years, the team had built a prototype of the soft-capture hardware and verified the control system that will be used to control the soft-capture system. In 2001, the LIDS team was tasked to work with the X- 38 Crew Return Vehicle (CRV) project and build its first Engineering Development Unit (EDU).

LaBauve, Tobie E.↗
NASA NTRS2005

Distributed Adaptive Control: Beyond Single-Instant, Discrete Variables

In extensive form noncooperative game theory, at each instant t, each agent i sets its state x, independently of the other agents, by sampling an associated distribution, q(sub i)(x(sub i)). The coupling between the agents arises in the joint evolution of those distributions. Distributed control problems can be cast the same way. In those problems the system designer sets aspects of the joint evolution of the distributions to try to optimize the goal for the overall system. Now information theory tells us what the separate q(sub i) of the agents are most likely to be if the system were to have a particular expected value of the objective function G(x(sub 1),x(sub 2), ...). So one can view the job of the system designer as speeding an iterative process. Each step of that process starts with a specified value of E(G), and the convergence of the q(sub i) to the most likely set of distributions consistent with that value. After this the target value for E(sub q)(G) is lowered, and then the process repeats. Previous work has elaborated many schemes for implementing this process when the underlying variables x(sub i) all have a finite number of possible values and G does not extend to multiple instants in time. That work also is based on a fixed mapping from agents to control devices, so that the the statistical independence of the agents' moves means independence of the device states. This paper also extends that work to relax all of these restrictions. This extends the applicability of that work to include continuous spaces and Reinforcement Learning. This paper also elaborates how some of that earlier work can be viewed as a first-principles justification of evolution-based search algorithms.

Wolpert, David H.↗
NASA NTRS2013

Systems and Methods for Peak-Seeking Control

A computerized system and method for peak-seeking-control that uses a unique Kalman filter design to optimize a control loop, in real time, to either maximize or minimize a performance function of a physical object ("plant"). The system and method achieves more accurate and efficient peak-seeking-control by using a time-varying Kalman filter to estimate both the performance function gradient (slope) and Hessian (curvature) based on direct position measurements of the plant, and does not rely upon modeling the plant response to persistent excitation. The system and method can be naturally applied in various applications in which plant performance functions have multiple independent parameters, and it does not depend upon frequency separation to distinguish between system dimensions.

Ryan, John J↗
NASA NTRS1995

Algorithms for high aspect ratio oriented triangulations

Grid generation plays an integral part in the solution of computational fluid dynamics problems for aerodynamics applications. A major difficulty with standard structured grid generation, which produces quadrilateral (or hexahedral) elements with implicit connectivity, has been the requirement for a great deal of human intervention in developing grids around complex configurations. This has led to investigations into unstructured grids with explicit connectivities, which are primarily composed of triangular (or tetrahedral) elements, although other subdivisions of convex cells may be used. The existence of large gradients in the solution of aerodynamic problems may be exploited to reduce the computational effort by using high aspect ratio elements in high gradient regions. However, the heuristic approaches currently in use do not adequately address this need for high aspect ratio unstructured grids. High aspect ratio triangulations very often produce the large angles that are to be avoided. Point generation techniques based on contour or front generation are judged to be the most promising in terms of being able to handle complicated multiple body objects, with this technique lending itself well to adaptivity. The eventual goal encompasses several phases: first, a partitioning phase, in which the Voronoi diagram of a set of points and line segments (the input set) will be generated to partition the input domain; second, a contour generation phase in which body-conforming contours are used to subdivide the partition further as well as introduce the foundation for aspect ratio control, and; third, a Steiner triangulation phase in which points are added to the partition to enable triangulation while controlling angle bounds and aspect ratio. This provides a combination of the advancing front/contour techniques and refinement. By using a front, aspect ratio can be better controlled. By using refinement, bounds on angles can be maintained, while attempting to minimize the number of Steiner points.

Posenau, Mary-Anne K.↗
NASA NTRS2015

Adsorption of Carbon Dioxide, Ammonia, Formaldehyde, and Water Vapor on Regenerable Carbon Sorbents

Results are presented on the development of reversible sorbents for the combined carbon dioxide, moisture, and trace‐contaminant (TC) removal for use in Extravehicular Activities (EVAs), and more specifically in the Primary Life Support System (PLSS). The currently available life support systems use separate units for carbon dioxide, trace contaminants, and moisture control, and the long‐term objective is to replace the above three modules with a single one. Furthermore, the current TC‐control technology involves the use of a packed bed of acid‐impregnated granular charcoal, which is nonregenerable, and the carbon‐based sorbent under development in this project can be regenerated by exposure to vacuum at room temperature. In this study, several carbon sorbents were fabricated and tested for simultaneous carbon dioxide, ammonia, formaldehyde, and water sorption. Multiple adsorption/vacuum‐regeneration cycles were demonstrated at room temperature, and also the enhancement of formaldehyde sorption by the presence of ammonia in the gas mixture.

Wojtowicz, Marek A.↗
NASA NTRS2018

A Prognostics Framework Development for Swarm Satellite Formations

Prognostics is the science of predicting the failure(s) of a component or a system and understanding how the performance will change in the event of a failure or degradation mechanism. With accurate predictions of possible failures, autonomous mitigative actions can be taken to correct/repair any issues or alert human operators of a failure threshold exceedance requiring condition-based maintenance. Although there is extensive research on failure predictions for a component or a system, there are significantly more opportunities to foray into failure predictions and prognostics for a system of systems such as an airspace consisting of multiple aircraft, a fleet of unmanned aerial vehicles, and a swarm of intelligent satellite systems. Failure prediction and mitigation are particularly important in autonomous systems such as satellite swarm systems that need effective resource management and minimal human interactions. Based on NASA's decadal survey, there is a clear need to prioritize the development of satellite swarm technology for studies of space physics and Earth science. The science community will propose future missions that return in-situ measurements from a 3-D (three-dimensional) volume of space, with relative spacecraft motion and inter-satellite baselines controlled according to the mission objectives. For such multi-spacecraft missions, it is required that ground operations resources do not scale with the number of satellites, thus compromising the swarm or leading to inefficiencies in resource allocation. Swarms of tens or hundreds of small satellites will require autonomy in attitude control, navigation and failure. Although significant research has been conducted in the areas of autonomous formation flying algorithms, less attention has been given to the development of resilient systems robust to failures.The focus of this research paper is the integration of model-based prognostics into the swarm dynamics control and decision-making algorithms. We simulate swarm management strategies for a subsystem failure to demonstrate the importance of failure predictions by comparing two cases: (i) no health information is provided to the system and utilized in the decision-making process and (2) system health information is obtained using prognostics and employed by the control system. One example scenario presented is for the GPS (Global Positioning System) system of an individual satellite to perform off-nominally due to increasing estimated error. In this scenario, the keep-out zone for that satellite would become more conservative, thereby decreasing the risk of collision. This is achieved via tuning the individual artificial repulsive functions assigned to each satellite.This paper is structured as follows. First we provide an overview of current swarm technology development, where we specifically use the term swarm to define multiple satellites flying in formation in similar orbits, with cross-link communication and station-keeping capabilities. Second, we give an introduction to the Swarm Orbital Dynamics Advisor (SODA), a tool that accepts high-level configuration commands and provides the orbital maneuvers required to achieve the prescribed formation configuration. Third, we provide the details of the model-based prognostics algorithm implementation in SODA. Finally, we present different case studies for potential component/subsystem failures and the swarm responses based with and without failure prediction information.

prognostics↗
NASA NTRS2004

Test Rig for Evaluating Active Turbine Blade Tip Clearance Control Concepts

The objectives of the research presented in this viewgraph presentation are to 1) Design a mechanical ACC system for HPT tip seal clearance management; 2) Design a test rig to evaluate ACC system concepts. We have focused our efforts on designing mechanical ACC systems that articulate the seal shroud via mechanical linkages connected to actuators that reside outside the extreme environment of the HPT. We opted for this style of design due to a lack of high temperature/low profile actuators that are presently available. We have also selected multiple hydraulic actuators for this first generation ACC system. Fuel-draulic actuators are already a well established technology.

Lattime, Scott B.↗
NASA NTRS2013

GFEChutes Lo-Fi

NASA needed to provide a software model of a parachute system for a manned re-entry vehicle. NASA has parachute codes, e.g., the Descent Simulation System (DSS), that date back to the Apollo Program. Since the space shuttle did not rely on parachutes as its primary descent control mechanism, DSS has not been maintained or incorporated into modern simulation architectures such as Osiris and Antares, which are used for new mission simulations. GFEChutes Lo-Fi is an object-oriented implementation of conventional parachute codes designed for use in modern simulation environments. The GFE (Government Furnished Equipment), low-fidelity (Lo-Fi) parachute model (GFEChutes Lo-Fi) is a software package capable of modeling the effects of multiple parachutes, deployed concurrently and/or sequentially, on a vehicle during the subsonic phase of reentry into planetary atmosphere. The term "low-fidelity" distinguishes models that represent the parachutes as simple forces acting on the vehicle, as opposed to independent aerodynamic bodies. GFEChutes Lo-Fi was created from these existing models to be clean, modular, certified as NASA Class C software, and portable, or "plug and play." The GFE Lo-Fi Chutes Model provides basic modeling capability of a sequential series of parachute activities. Actions include deploying the parachute, changing the reefing on the parachute, and cutting away the parachute. Multiple chutes can be deployed at any given time, but all chutes in that case are assumed to behave as individually isolated chutes; there is no modeling of any interactions between deployed chutes. Drag characteristics of a deployed chute are based on a coefficient of drag, the face area of the chute, and the local dynamic pressure only. The orientation of the chute is approximately modeled for purposes of obtaining torques on the vehicle, but the dynamic state of the chute as a separate entity is not integrated - the treatment is simply an approximation. The innovation in GFEChutes Lo-Fi is to use an object design that closely followed the mechanical characteristics and structure of a physical system of parachutes and their deployment mechanisms. Software objects represent the components of the system, and use of an object hierarchy allows a progression from general component outlines to specific implementations. These extra chutes were not part of the baseline deceleration sequence of drogues and mains, but still had to be simulated. The major innovation in GFEChutes Lo-Fi is the software design and architecture.

Gist, Emily↗
NASA NTRS2014

Carbon-Based Regenerable Sorbents for the Combined Carbon Dioxide and Ammonia Removal for the Primary Life Support System (PLSS)

Results are presented on the development of reversible sorbents for the combined carbon dioxide and trace-contaminant (TC) removal for use in Extravehicular Activities (EVAs). Since ammonia is the most important TC to be captured, data on TC sorption presented in this paper are limited to ammonia, with results relevant to other TCs to be reported at a later time. The currently available life support systems use separate units for carbon dioxide, trace contaminants, and moisture control, and the long-term objective is to replace the above three modules with a single one. Furthermore, the current TC-control technology involves the use of a packed bed of acid-impregnated granular charcoal, which is non-regenerable, and the carbon-based sorbent under development in this project can be regenerated by exposure to vacuum at room temperature. The objective of this study was to demonstrate the feasibility of using carbon sorbents for the reversible, concurrent sorption of carbon dioxide and ammonia. Several carbon sorbents were fabricated and tested, and multiple adsorption/vacuum-regeneration cycles were demonstrated at room temperature, and also a carbon surface conditioning technique that enhances the combined carbon dioxide and ammonia sorption without impairing sorbent regeneration.

Wojtowicz, Marek A.↗