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At least 379 records · Page 21

Data Center High-Temperature Liquid Cooling and Heat Reuse Techno-Economic Study: Preprint

Data centers are energy-intensive facilities with growing demands for efficiency and cost-effective operations. Smaller, more distributed edge inference data centers are expected to proliferate as AI applications require low latency closer to the user of AI tools, which presents a growing opportunity to explore the systems implications of liquid cooling on water and energy use. This study analyzes the implementation of high-temperature liquid cooling systems in a prototypical inference 1-MW data center and explores the potential for heat reuse across varying climates with a goal to optimize energy efficiency, reduce capital and operational costs, and identify opportunities for high-performance cooling and water use reduction infrastructure. This analysis evaluated configurations utilizing a peak day hourly sizing and systems performance spreadsheet to evaluate design and operational conditions from which component sizes, installed cost, operational cost, and performance metrics were determined for the Base case and the Elevated case. The techno-economic analysis included heat reuse applications across a range of heat recovery temperatures and heat rejection options. The analysis shows that high-temperature liquid cooling allows for improved energy efficiency, lower water consumption, and lower capital costs compared to traditional cooling approaches. Transitioning to elevated water inlet/outlet temperatures (50 degrees C/60 degrees C) eliminates the need for chillers, cooling towers, and heat recovery equipment in many scenarios across three distinct climate zones. This results in up to 75% capital cost savings for the cooling and heat recovery equipment, and with significantly reduced water consumption, especially in non-heat reuse applications. Heat generated from data centers can also be repurposed for space heating, domestic hot water, and other applications, and is most cost-effective when data center outlet temperatures exceed 55-60 degrees C.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Numerical Analysis of Fuel Effects on Advanced Compression Ignition Using a Cooperative Fuel Research Engine Computational Fluid Dynamics Model

Growing environmental concerns and demand for a better fuel economy are driving forces that motivate the research for more advanced engines. Multi-mode combustion strategies have gained attention for their potential to provide high thermal efficiency and low emissions for light-duty applications. These strategies target optimizing the engine performance by correlating different combustion modes to load operating conditions. The extension from boosted spark ignition (SI) mode at high loads to advanced compression ignition (ACI) mode at low loads can be achieved by increasing the compression ratio and utilizing intake air heating. Further, in order to enable an accurate control of intake charge condition for ACI mode and rapid mode-switches, it is essential to gain fundamental insights into the autoignition process. Within the scope of ACI, homogeneous charge compression ignition (HCCI) mode is of significant interest. It is known for its potential benefits, operation at low fuel consumption, low NOx, and particulate matter (PM) emissions. In the present work, a virtual Cooperative Fuel Research (CFR) engine model is used to analyze fuel effects on ACI combustion. In particular, the effect of fuel octane sensitivity (S) (at constant Research Octane Number (RON)) on autoignition propensity is assessed under beyond-RON (BRON) and beyond-MON (BMON) ACI conditions. The three-dimensional CFR engine computational fluid dynamics (CFD) model employs a finite-rate chemistry approach with a multi-zone binning strategy to capture autoignition. Two binary blends with Research Octane Number (RON) of 90 are chosen for this study: primary reference fuel (PRF) with S = 0 and toluene–heptane (TH) blend with S = 10.8, representing paraffinic and aromatic gasoline surrogates. Reduced mechanisms for these blends are generated from a detailed gasoline surrogate kinetic mechanism. Simulation results with the reduced mechanisms are validated against experimental data from an in-house CFR engine, with respect to in-cylinder pressure, heat release rate, and combustion phasing. Thereafter, the sensitivity of combustion behavior to ACI operating condition (BRON versus BMON), air-fuel ratio (λ = 2 and 3), and engine speed (600 and 900 rpm) is analyzed for both fuels. It is shown that the sensitivity of a fuel’s autoignition characteristics to λ and engine speed significantly differs at BRON and BMON conditions. Moreover, this sensitivity is found to vary among fuels, despite the same RON. It is also observed that the presence of low-temperature heat release (LTHR) under BRON condition leads to more sequential autoignition and longer combustion duration than BMON condition. Finally, the study indicates that the octane index (OI) fails to capture the trend in the variation of autoignition propensity with S under the BMON condition.

33 ADVANCED PROPULSION SYSTEMS↗

MULTI-DIMENSIONAL MODELING OF THE CFR ENGINE FOR THE INVESTIGATION OF SI NATURAL GAS COMBUSTION AND CONTROLLED END-GAS AUTOIGNITION

Engine knock and misfire are barriers to pathways leading to high-efficiency Spark-Ignited (SI) Natural Gas engines. The general tendency to knock is highly dependent on engine operating conditions and the fuel reactivity. The problem is further complicated by low emission limits and the wide range of chemical reactivity in pipeline quality natural gas. Depending on the region and the source of the natural gas, its reactivity, described by its methane number (analogous to the octane number for liquid SI fuels) can span from 65 - 95. In order to realize diesel-like efficiencies, SI natural gas engines must be designed to operate at high BMEP near knock limits over a wide range of fuel reactivity. This requires a deep understanding regarding the combustion-engine interactions pertaining to flame propagation and end-gas autoignition (EGAI). However, EGAI, if controlled, provides an opportunity to increase SI natural gas engine efficiency by increasing combustion rate and the total burned fuel, mitigating the effects of the slow flame speeds of natural gas fuels which generally reduce BMEP and increase unburned hydrocarbon emissions. For this reason, in order to study EGAI phenomenon, the present work highlights multi-dimensional computational fluid dynamics (CFD) models of the Cooperative Fuel Research (CFR) engine. The CFR engine models are used to investigate fuel-engine interactions that lead to EGAI with natural gas, including effects of fuel reactivity, engine operating parameters, and exhaust gas recirculation (EGR). A Three-Pressure Analysis, performed with GT-Power, was used to estimate initial and boundary conditions for the three-dimensional CFD model. CONVERGE CFD v2.4 was used for the three-dimensional CFD modeling where the level set G-Equation model and SAGE detailed chemical kinetics solver were used. An assessment of the different modeling approaches is also provided to evaluate their limitations, advantages and disadvantages, and for which situations they are most applicable. Model validation was performed with experimental data taken with a CFR engine over varying compression ratio, CA50, EGR fraction, and IMEP and shows good agreement in Peak Cylinder Pressure (PCP), PCP crank angle, and the location of the 10%, 50%, and 90% mass fraction burned (CA10, CA50, and CA90, respectively). The models can predict the onset crank angle and pressure rise rate for light, medium, and heavy EGAI under a variety of fuel reactivities and engine operating conditions.

Bestel, Diego↗

Accelerating kinetic plasma simulations with machine-learning-generated initial conditions

Computational models of plasma technologies often solve for the system operating conditions by time-stepping an initial value problem to a quasi-steady solution. However, the strongly nonlinear and multi-timescale nature of plasma dynamics often necessitate millions, or even hundreds of millions, of steps to reach convergence, reducing the effectiveness of these simulations for computer-aided engineering. We consider acceleration of kinetic plasma simulations via data-driven machine-learning-generated initial conditions, which initialize the simulations close to their final quasi-steady-state, thereby reducing the number of steps to reach convergence. Three machine-learning models are developed to predict the density and ion kinetic profiles of capacitively coupled plasma discharges relevant to the microelectronics industry. The models are trained on kinetic simulations over a range of device operating frequencies and pressures. Best performance was observed when simulations were initialized with ion kinetic profiles generated by a convolutional neural network, reducing the mean number of steps to reach convergence by 17.1× when compared to initialization with a zero-dimensional global model. We also outline a workflow for continuous data-driven model improvement and simulation speedup, with the aim of generating sufficient data for full device digital twins.

Artificial neural networks↗

Multilayer Architecture Barriers for High Temperature Nuclear Applications

Innovative thin film multilayer metal/ceramic barrier coatings have been developed by Argonne National Laboratory to protect fuel cladding against different phenomena that can be encountered under the harsh operating conditions of advanced nuclear reactors. One phenomenon is Fuel-Cladding Chemical Interaction (FCCI), which can represent a challenge to the performance of steel-clad metallic fuels in sodium-cooled fast reactors (SFRs), especially when operating to high burnups at elevated cladding temperatures, and long fuel residence time. Another phenomenon is the corrosion of zirconium-based cladding under prototypic boiling water reactor (BWR) conditions and associated cladding during off normal conditions, including loss of coolant accidents (LOCA). This work provides details of the development and testing of a thin film (few microns) multilayer metal/ceramic (CrY/Y 2 O 3 ) coatings on steel cladding and its performance against FCCI. The coating architecture evolved through systematic mechanical testing, radiation tolerance assessments, and high-temperature diffusion studies from a preliminary multilayer concept to an optimized high-performance design. The optimized structure leverages stoichiometric Y 2 O 3 for its exceptional radiation stability, chemical inertness, and ultra-low fission product diffusivity (e.g., Ce diffusivity ~10 -20 m 2 /s in irradiated Y 2 O 3 at 650 °C). This is paired with ductile chromium-rich interlayers (Cr 95 Y 5 ), which significantly enhance fracture toughness and mechanical resilience. Design refinements, including increased ceramic layer thickness and optimized Cr–Y interlayer composition, eliminated fracture propagation and preserved coating integrity under extreme mechanical stress (>10× typical reactor conditions) and prolonged radiation exposure (~300 dpa). Those conditions are well beyond expected conditions during normal operations in SFR, and cover some of the transient conditions as well. In addition, the coating deposition was demonstrated to be applied uniformly to the inner surface of steel tubes representing prototypic SFR cladding. Another phenomenon under consideration in this work is the corrosion of zirconium-based cladding under prototypic boiling water reactor (BWR) conditions and associated off normal conditions including loss of coolant accident (LOCA). Another multilayer thin film coating is considered for mitigation of this phenomenon, where a coating of yttrium aluminum and yttrium aluminum ceramic/metal thin film coating. Preliminary results on the coating performance during high temperature thermal cycling (up to 1000 C) have shown promising performance of the coating. On-going optimization of the coating will continue in FY26.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Recent advances in CO 2 hydrogenation to value-added products — Current challenges and future directions

Climate change, global warming, fossil fuel depletion and rising fuel prices have created great incentives to seek alternative fuel production technologies. CO 2 transformation to value-added products using renewable H 2 has proven to be an emerging solution to enable this goal. In this regard, three different promising processes, namely methane, methanol and hydrocarbon synthesis via CO 2 hydrogenation are thoroughly discussed. In addition, the influential factors affecting process efficiencies such as catalyst design and mechanistic insight, operating conditions as well as reactor types are investigated, with key pathways that dictate catalyst activity and selectivity of the most promising materials described. Furthermore, a brief overview of the reactor configuration and its crucial role in the improving process viability is analyzed. Accordingly, fixed-bed, fluidized-bed, annular and spherical reactors along with H 2 O/H 2 perm-selective membrane reactors are disscussed for hydrocarbon production. In addition, different reactor configurations are compared to assess the best one that is adjustable depending on the reaction mechanism. In conclusion, a corrugated-wall dual-type membrane reactor is proposed as an emerging alternative for CO 2 hydrogenation to value-added products.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Toward Carbon Monoxide Methanation at Mild Conditions on Dual-Site Catalysts

The catalytic carbon monoxide (CO) methanation is an ideal model reaction for the fundamental understanding of catalysis on the gas–solid interface and is crucial for various industrial processes. However, the harsh operating conditions make the reaction unsustainable, and the limitations set by the scaling relations between the dissociation energy barrier and dissociative binding energy of CO further increase the difficulty in designing high-performance methanation catalysts operating under milder conditions. In this work, we proposed a theoretical strategy to circumvent the limitations elegantly and achieve both facile CO dissociation and C/O hydrogenation on the catalyst containing a confined dual site. The DFT-based microkinetic modeling (MKM) reveals that the designed Co-Cr 2 /G dual-site catalyst could provide 4–6 orders of magnitude higher turnover frequency for CH 4 production than the cobalt step sites. We believe that the proposed strategy in the current work will provide essential guidance for designing state-of-the-art methanation catalysts under mild conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Design of a Two-Body Wave Energy Converter Featuring Controllable Geometry

While the field of wave energy has been the subject of numerical simulation, scale model testing, and precommercial project testing for decades, wave energy technologies remain in the early stages of development and must continue to prove themselves as a promising modern renewable energy field. A wave energy converter (WEC) concept currently being explored is the variable-geometry WEC (VGWEC), which aims to add an extra control option to WEC design. VGWECs attempt to incorporate controllable geometric features to adjust the floating body hydrodynamics to favor either power absorption, load shedding, or other operational goals. These variable geometry components have been proposed to be controlled on a sea-state-to-sea-state or wave-to-wave time scale depending on the force (or torque) and bandwidth limitations of the actuators required to manipulate just the controllable geometric hull features. Having control over both the WEC geometry components and the power takeoff (PTO) offers the potential to improve overall system performance and reliability if a cost-effective solution can be found for a given WEC architecture. This paper will present the recent developments and results of a VGWEC concept that incorporates variable-geometry modules into a two-body WEC. In the proposed VGWEC concept, the variable-geometry modules consist of air-inflatable bags in the surface float and a water inflatable ring in the subsurface body. The surface float is tethered directly to the subsurface body through tether lines, each connected to a separate PTO. Adjusting the geometry of both the surface and subsurface bodies along with the PTO coefficients can maximize power in design sea states while reducing motion response and PTO forces when transitioning to sea states where rated power is reached and load shedding is prioritized. The ability to transition between operating condition is expected to increase the sea state operational map and power capacity.

geometry control↗

Design and Modeling of an 80 bar Oxy-Combustor for Direct Fired Supercritical CO2 Applications

As supercritical CO2 power cycles for fossil energy power generation continue to generate interest, there are significant issues and unanswered questions regarding injector design, flame stabilization, wall heat transfer, CO emissions, combustion dynamics and other combustion phenomenon. For natural gas, direct-fired cycles with carbon capture it is believed that Computational Fluid Dynamics (CFD) modeling will play an essential role in the combustor design process. To accurately model turbulent reacting flows at these unique conditions, experimental data is needed to validate CFD codes and sub-models and is currently lacking at conditions relevant for these cycles. This paper presents the conceptual design and CFD simulations of an experimental 80 bar oxy-combustion facility and test article currently under construction at NETL. The facility is targeted towards the testing of a single injector, direct-fired sCO2 combustor at the 100 kW thermal output level. While these conditions do not reflect the actual Allam cycle operating conditions (300 bar) they are viewed as a stepping stone in the model validation process at supercritical conditions. Reynolds Averaged Navier-Stokes as well as Large Eddy Simulation are used to model the turbulent combustion process and aid in the design of the combustor and injector. Process parameters including oxidizer preheat temperature and combustor flowrate are investigated.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Design of a Meso-Scale Test of a Fracture Thermal Energy Storage (FTES) System

This paper will present the characterization, scaling, and design of an intermediate-scale field test of a fracture thermal energy storage system (FTES). Seasonal storage of thermal energy has the potential to both significantly reduce the total energy requirements for heating and cooling of buildings, but also allow for the flexibility to store thermal energy from intermittent sources. With approximately half of global energy consumption currently being used for heating and cooling, this represents an important path to reducing greenhouse gas (GHG) emissions. The concept of FTES is to drill two or more wells into a low permeability formation, generally at a depth of less than a few hundred meters, and then generate hydraulic fractures to create flow paths for water to circulate between the wells. Hot or cold thermal energy can then be stored in the surrounding rock mass by circulating hot or cold water through the fractures, which will heat or cool the rock mass. To recover the stored energy, ambient temperature water can be then circulated through the fractures, which will then be heated or cooled by the rock mass. Fractures inherently have a very large ratio of surface area to volume. This allows for very high heat fluxes to and from the rock mass to be achieved despite the relatively low thermal conductivity of most geologic formations. Because large fractures can be made with low-cost equipment and with only inexpensive and environmentally safe materials such as water and sand, the cost to construct even large FTES systems is expected to be quite low. This paper will present what the performance requirements, size, and operating conditions of a full-scale system to operate a commercial building. The paper will describe how these full-scale system characteristics will be used as a design basis for an intermediate-scale FTES test to be conducted at the Sanford Underground Research Facility (SURF) in Lead, SD.

Burghardt, Jeffrey A.↗

Daily operational impacts on battery degradation in heavy-duty electric drayage trucks

Battery aging is a critical factor influencing the performance, longevity, and cost of ownership of battery electric trucks (BETs). This paper presents a comprehensive evaluation of battery aging for two Li-ion battery chemistries, Nickel-Manganese-Cobalt (NMC) and Lithium-Iron-Phosphate (LFP), accounting for both cycling and calendar aging. In contrast to traditional methods that rely on simplified linear degradation models based on manufacturer-provided data, this study employs semi-empirical aging models calibrated to experimentally collected data. The models are integrated into a detailed vehicle simulation environment, enabling a comprehensive assessment of battery degradation under realistic operating conditions. A case study focusing on heavy-duty electric drayage truck operations in the Port of Savannah, GA, is presented to illustrate the impact on battery pack lifespan of: seasonal variations, daily operational activities, charging strategies, and battery storage conditions. The results illuminate the significance of the battery pack’s state of charge during stationary periods, such as overnight storage or weekend parking, on battery degradation and its potential implications for long-term vehicle viability. Additionally, the study explores how different operational and environmental factors affect battery degradation, offering critical insights into best battery charging and storage practices. Our results demonstrate that LFP outperforms NMC in terms of years of useful life; however, by utilizing charging strategies that minimize the amount of time the battery spends resting at high levels of state-of-charge, the lifespan of the battery pack that uses NMC can nonetheless be increased by more than a factor of two.

25 ENERGY STORAGE↗

Single Primary Heat Extraction and Removal Emulator (SPHERE) Long Duration Testing

For the development of heat-pipe cooled microreactors, it is crucial to thoroughly understand the characteristics and functioning of heat pipes across a wide spectrum of operating conditions. Passive heat removal and its long-term performance stability are critical factors in this context. Enhanced experimental data is vital for evaluating the operational lifespan of alkali metal heat pipes. Idaho National Laboratory (INL) has successfully conducted an extended duration test on a high-performance sodium-filled heat pipe, closely monitoring the axial temperature profile, power supplied by the heaters, and heat removed by a gas-gap calorimeter. The results from this testing provide valuable data that are instrumental in supporting heat pipe validation efforts. Specifically, this data aids in the development and validation of Sockeye, the Multiphysics Object-Oriented Simulation Environment (MOOSE) tool under the US-DOE NEAMS program designed for heat pipe modeling. By comparing experimental results with Sockeye’s predictions, the tool's accuracy and reliability can be assessed and improved, thereby enhancing its capability to simulate heat pipe operations under various conditions.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Topology optimization of compliant mechanisms under transient thermal conditions

This work considers multi-material topology optimization of compliant mechanisms under transient thermal and quasi-static mechanical conditions wherein thermally actuated devices are optimized for different operating conditions. The materials are modeled using finite strain thermo-hyperelasticity and a two way coupling between the energy balance and equilibrium equations is investigated. The design updates are generated from the gradient-based method of moving asymptotes optimizer and the sensitivities are computed using the time dependent adjoint sensitivity analysis. Results show the impact of designing for short versus long actuation times.

42 ENGINEERING↗

Broadening of the drumhead-mode spectrum due to in-plane thermal fluctuations of two-dimensional trapped ion crystals in a Penning trap

Two-dimensional crystals of ions stored in Penning traps are a leading platform for quantum simulation and sensing experiments. For small amplitudes, the out-of-plane motion of such crystals can be described by a discrete set of normal modes called the drumhead modes, which can be used to implement a range of quantum information protocols. However, experimental observations of crystals with Doppler-cooled and even nearground- state-cooled drumhead modes reveal an unresolved drumhead-mode spectrum. In this work, we establish in-plane thermal fluctuations in ion positions as a major contributor to the broadening of the drumhead-mode spectrum. In the process, we demonstrate how the confining magnetic field leads to unconventional in-plane normal modes, whose average potential and kinetic energies are not equal. This property, in turn, has implications for the sampling procedure required to choose the in-plane initial conditions for molecular-dynamics simulations. Further, for current operating conditions of the NIST Penning trap, our study suggests that the two-dimensional crystals produced in this trap undergo in-plane potential-energy fluctuations of the order of 10mK. Our study therefore motivates the need for designing improved techniques to cool the in-plane degrees of freedom.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Comparative Structural Rigidity Analysis of the NBSR DDE and the NBSR LEU Fuel Element

The National Bureau of Standards Reactor (NBSR) is a 20-MW heavy-water moderated and cooled, enriched-fuel, tank-type reactor located in the NIST Center for Neutron Research laboratory complex. NBSR is one of six U.S. high performance research reactors (USHPRR), including one critical facility, that actively collaborates with the National Nuclear Security Administration (NNSA) Material Management and Minimization (M3) Reactor Conversion Program to convert from the use of highly enriched uranium fuel to the use of low-enriched uranium (LEU, < 20 wt% U-235) fuel. On the LEU U-10Mo fuel qualification side, mini-plate and large-plate irradiations have been successfully performed, and more experiments are either ongoing or planned. As an additional experimental campaign to support licensing of the LEU fuel for the use in the NBSR, the NBSR Design Demonstration Element (DDE) will be a full-sized test element similar to the NBSR LEU fuel element and irradiated in a test reactor under conditions as prototypic of the NBSR LEU fuel element operating conditions as possible.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Use of Machine Learning for Signature Development in a Multi-Sensor Environment for Safeguard Applications of Solvent Extraction Processes

Idaho National Laboratory is constructing the Special Nuclear Material test bed (Beartooth) for research and development pertaining to nuclear fuel processing operations using centrifugal contactors. Beartooth will enable give researchers the opportunity to study the dissolution, separation, and conversion of special nuclear materials (e.g., plutonium, enriched uranium, and thorium). As a lead-in to Beartooth, this project constructed a test bed to study the process and equipment behavior with real time series data collection using a variety of non-traditional sensors, in order to identify process failures and label them as either accidental or purposeful, thus enhancing nuclear nonproliferation stewardship. The measurement sources in this test bed include vibration, acoustic, current, flow, colorimetric, and thermal data. These measurements vary in terms of magnitude, frequency, and location. This information will be combined and used within data-driven machine-learning methods to detect operation condition changes that are either intentional (i.e., changes in operating set points) or malicious (i.e., flow diversion) in nature. This presentation covers the data processing and signature development activities necessary for utilizing this heterogeneous dataset to classify process anomalies.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Grid Forming Control of PMSG-based Wind Turbines under Fault Conditions

Grid-forming control is widely envisioned as core technology ensuring stable operation of future power systems with increasing deployment of converter-interfaced renewable generation. However, research on grid forming control of wind turbines, especially under faults, is still in its early stages. In this context, this paper augments dual-port grid-forming control for type IV wind turbines with auxiliary controls to enable reliable fault ride through capabilities. In particular, the proposed control does not require a dc chopper or mode switching to grid-following control. Instead, energy-balancing dual-port GFM control is augmented with active rotor speed damping control and threshold virtual impedance for current limiting during faults. Different operating conditions of wind turbines are considered in a detailed electromagnetic transient simulation study to validate the effectiveness of the proposed control.

Lyu, Xue↗

Enhancing methane production of anaerobic digested sewage sludge by advanced wet oxidation & steam explosion pretreatment

Anaerobic digestion (AD) of sewage sludge is associated with lowered carbon conversion efficiency due to the recalcitrance of microbial cells in the Waste Activated Sludge (WAS) from the aeration basins with 50 % of the dry weight still being present after AD. The effect of Advanced Wet Oxidation & Steam Explosion (AWOEx) pretreatment on the methane yield at variable temperatures (165–200 °C), residence time (15–45 min) and oxygen dosage (1%–10% based on VS concentration) was tested in this study. Central composite design (JMP® Pro) was used to design 19 runs of AWOEx pretreatment of dewatered digested sewage sludge (DADSS) at different operating conditions. After pretreatment the DADSS was fed to 19 bioreactors operated in semi-continues mode at 37 °C. The highest average methane yields of 183 mL/g VS and 170 mL/g VS were found for the bioreactors receiving DADSS pretreated at 165 °C with a retention time of 15 min and 10 % O2 (Condition 1), and, 182.5 °C with a retention time of 15 min and 5.5 % O2 (Condition 2). This corresponds to an increase in the methane production of 156.2 % and 140.5 % compared to the methane production from the DADSS without pretreatment.

09 BIOMASS FUELS↗