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FEMP developed this Federal Water Management Planning Manual to provide a resource for designing a comprehensive water management program. The manual describes strategies to optimize water use at federal facilities, use water balance analysis methods, identify design elements and procurement best practices, and expand use of alternative water.
The US Department of Energy Office of Electricity has partnered with Oak Ridge National Laboratory (ORNL) to find alternative precision timing solutions for the nation’s power grid. This effort is in response to the vulnerabilities identified in the Global Navigation Satellite System (GNSS), of which the US Global Positioning System (GPS) platform is a part. Additionally, Executive Order 139055 has highlighted the need for alternative or backup timing solutions. ORNL has established a Timing Lab and has been testing various technologies and timing devices as part of this effort. Precision Time Protocol (PTP), and the off-the-shelf timing devices and network connections that support it, are among the alternatives being tested. This work reports the accuracy of PTP over an Optical Transport Network (OTN) and is part of a series published by the Center for Alternative Synchronization and Timing (CAST).
Triacetic acid lactone (TAL) is a versatile platform chemical traditionally biosynthesized via decarboxylative Claisen condensation by 2-pyrone synthase. However, this route is limited by poor efficiency and dependence on malonyl-CoA. Here, we show that non-decarboxylative Claisen condensation by polyketoacyl-CoA thiolases offers a more efficient alternative. Through mining homologs of a previously reported enzyme from Cupriavidus necator, we identify five thiolases with TAL production activity. One candidate, BktBbr from Burkholderia sp. RF2-non_BP3, exhibits approximately 30-fold higher activity in vitro and supports 30-fold higher TAL titers in Escherichia coli compared to the original enzyme. Fed-batch fermentation achieves titers up to 2.8 g L⁻¹. Structural analysis of BktBbr co-crystallized with CoA esters guides rational engineering to further enhance performance. Our discovery of a highly active thiolase establishes an alternative enzymatic route to produce TAL efficiently, providing a scalable foundation for sustainable biomanufacturing.
Classification systems can be an important tool for identifying and quantifying the importance of relationships, assessing spatial patterns in a standardized way, and forecasting alternative decision scenarios to characterize the potential benefits (e.g., ecosystem services) from ecosystem restoration that improve human health and well-being. We present a top-down approach that systematically leverages ecosystem services classification systems to identify potential services relevant for ecosystem restoration decisions. We demonstrate this approach using the U.S. Environmental Protection Agency’s National Ecosystem Service Classification System Plus (NESCS Plus) to identify those ecosystem services that are relevant to restoration of tidal wetlands. We selected tidal wetland management documents from federal agencies, state agencies, wetland conservation organizations, and land stewards across three regions of the continental United States (northern Gulf of Mexico, Mid-Atlantic, and Pacific Northwest) to examine regional and organizational differences in identified potential benefits of tidal wetland restoration activities and the potential user groups who may benefit. We used an automated document analysis to quantify the frequencies at which different wetland types were mentioned in the management documents along with their associated beneficiary groups and the ecological end products (EEPs) those beneficiaries care about, as defined by NESCS Plus. Results showed that a top combination across all three regions, all four organizations, and all four tidal wetland types was the EEP naturalness paired with the beneficiary people who care (existence). Overall, the Mid-Atlantic region and the land steward organizations mentioned ecosystem services more than the others, and EEPs were mentioned in combination with tidal wetlands as a high-level, more general category than the other more specific tidal wetland types. Certain regional and organizations differences were statistically significant. Those results may be useful in identifying ecosystem services-related goals for tidal wetland restoration. This approach for identifying and comparing ecosystem service priorities is broadly transferrable to other ecosystems or decision-making contexts.
Here, advancing separations science is important for the entire field of chemistry. One partitioning technique that would benefit from improvement is solvent extraction. Despite its effective and widespread use, the method suffers from some problems: generation of flammable organic waste, lengthy process times, and safety concerns associated with contacting organic solvents with acidic aqueous solutions. We developed an alternative separation method inspired by solvent extraction that side-steps those issues. Toward this end, we identified that the functionality of an extractant (an agent used in solvent extraction to pull analytes from the aqueous phase into the organic phase) would change if it was modified for water solubility. In this alternative scenario, the extractant transforms into an “aqueous solubilizing agent.” We discovered that adding this aqueous solubilizing agent alongside a precipitating agent caused the contaminants to precipitate, but not the analyte. This separation concept was demonstrated within the bounds of one of the most difficult partitioning problems, separating minor actinides (Am 3+ ) from lanthanides (Ln 3+ ). We discovered that the (HSO 3 Ph) 4 BTP (aq) aqueous solubilizing agent prevented Am 3+ (aq) from precipitating with Ln 3+ (aq) when f-element precipitating agents (NaF (aq) or HF (aq) ) were added. This separation boasts impressive Am 3+ (aq) recovery yield (90 ± 2 %), near quantitative Ln 3+ (aq) removal, and high separation factors [>3000, Am 3+ (aq) vs. Nd 3+ (aq) ]. It seems likely – given the large number of candidate extractants that could be modified for aqueous solubility and the numerous combinations of existing solubilizing and precipitating agents – that this alternative approach could be used broadly in place of solvent extraction and solve other important separation problems.
Washington State Department of Ecology (Ecology) requested that U.S. Department of Energy (DOE)-Office of River Protection (ORP) consider an evaluation of effects of fine-grained thin sediment layers on transport with a separate alternative conceptual model in its evaluation of the potential impact of tank leaks and other unplanned releases within the tank farm at the Hanford Site. For this alternative model, Ecology recommended that the model be developed based on the general framework of fine-grained units identified by a stakeholder group in their interpretations of variability in moisture content data collected in the vicinity of Waste Management Area (WMA) C. In discussions with DOE-ORP, Ecology acknowledged that the underlying data and interpretations of the occurrence and lateral continuity of the fine-grained thin layers identified by a stakeholder group are uncertain. However, DOE-ORP agreed to Ecology's recommendation and has provided support for the requested evaluation that involved development of an alternative model based on the general framework of the unpublished report by the stakeholder. DOE-ORP considered this evaluation to be a hypothetical evaluation of vadose zone heterogeneities at WMA C. General observations from the range of simulation cases examined in the evaluation of the effects of hypothetical vadose zone heterogeneities at WMA C are as follows. - The movement of the center of mass of the simulated plumes was generally vertically downward below the source for all simulations, including those that incorporated the hypothetical fine-grained units. - All simulations that incorporated hypothetical heterogeneity produced additional plume spreading over what was produced in simulations using Equivalent Homogeneous Media (EHM) model(s)a. The spreading resulted in a broadening of the fringes of the plume, resulting in a wider region of low concentration, but lower peak concentrations associated with the center of mass of the plume. - Simulations that used the silty-sand hydraulic properties, suggested by Ecology for the hypothetical fine-grained units, generally produced similar spreading and slightly lower peak mass flux at the water table when compared to the EHM modeling results. a The EHM-based models used at WMA C do not explicitly include small-scale fine-grained heterogeneities used in the model advocated by Ecology. - Simulations that used the silty-sand hydraulic properties, suggested by Ecology for the hypothetical fine-grained units, generally produced less spreading and an earlier arrival of mass flux at the water table when compared to the use of another set of hydraulic properties from a silty-sand sample collected at a nearby disposal facility. - The EHM representation of the vadose zone generally produced higher peak mass flux and an earlier occurrence of peak fluxes at the water table compared to all analyses incorporating additional hypothetical heterogeneity. Results of this alternative model evaluation of past leaks provided some insight into the transport effects of vadose zone heterogeneities at WMA C that helped resolve Ecology's comments and issues related to the effects of vadose zone heterogeneities on past leaks and losses from the WMA C tank farms area. (authors)
Commercial buildings consumed 36% of electricity, or 1.35 trillion kWh, in the United States in 2017, and almost 30% of this energy was wasted. Much of this loss can be attributed to inefficient heating ventilation and air conditioning (HVAC) systems. By improving the operational conditions of HVAC, significant savings can be achieved. However, most buildings and building equipment do not use costly sub-meters to monitor and address performance issues, and on-site auditing can be expensive and insufficient. Alternatively in this study, we propose a data-driven method to identify savings opportunities using only whole building meter data and without setting foot in the building. For this purpose, we introduced two algorithms that virtually quantify the value of a thermostat setpoint setback and HVAC rescheduling. Additionally, we developed novel methods for detecting occupancy patterns and quantifying the baseload of the HVAC operation. Using a clustering algorithm, we identified those buildings for which HVAC savings was significant and further categorized the buildings based on their potential for savings. A population study of over 432 commercial buildings demonstrated a median percentage energy savings of 1.6% from a baseload reduction and 2.1% from HVAC rescheduling. Additionally, results indicate that retail buildings have the highest potential for savings among the building types studied.
Non-targeted analysis of complex chemical mixtures can be difficult considering the convoluted nature of the matrix and the potential unknown chemical differences between samples or classes of samples. Ultrahigh pressure liquid chromatography coupled to quadrupole time-of-flight mass spectrometry (UHPLC-QTOF) is an ideal technique to probe chemical differences for a wide variety of samples. While UHPLC-QTOF can discover minute chemical differences down to low part per billion (ppb) concentrations with a high degree of confidence, the application of high-resolution mass spectrometry can yield massive amounts of information (∼ 10 gb per sample) that cannot be analyzed manually. Therefore, the application of chemometric techniques is mandatory for the interrogation of complex samples. Fisher's ratio (FR) assisted multivariate curve resolution-alternating least squares (MCR-ALS) was used to the discover and identify the chemical differences between two classes of materials: 1) a pond water matrix and 2) the matrix spiked with a pharmaceutical standard mix containing 17 compounds. Thirteen of the seventeen spiked compounds were discovered using FR analysis, and then five were successfully deconvoluted using MCR-ALS wherein the number of curves chosen were automatically determined using singular value decomposition (SVD). In conclusion, the use of an automated FR assisted MCR-ALS will aid in discovering trace levels of chemical components without the need for the researcher to provide potentially biased input which will aid in non-targeted workflow.
Grid state estimation is essential for effective control and management of distribution systems. While weighted least squares has been the conventional method for state estimation, sparsity-aware methods have become popular due to their superior performance with limited data. Matrix completion and compressed sensing-based state estimation approaches exploit the underlying smoothness in the state variables. However, classic matrix completion methods do not take into account the temporal correlation of system states. Compressed sensing methods, on the other hand, require an appropriate choice of sparsifying basis that may not be easy to identify. This paper proposes a blocktensor completion based framework which uses an alternative approach to estimate voltage phasor, power injections and branch currents. This approach utilizes the temporal correlation of the system states in a tensor trace-norm minimization formulation with power flow equations as constraints. Herein, feature scaling is introduced in the problem formulation to benefit from the improved sensitivity of the tensor trace norm to the matrix columns in the scaled unfoldings of the tensor. Weighted tensor norm is utilized to exploit the structures of the different unfoldings of the state measurement tensor to improve the voltage estimation. The estimation accuracy is further improved by alternatively estimating the tensor columns and increasing the available data at each stage in the tensor completion process. The proposed methods are evaluated on the IEEE-33, 37 test systems and a 100- node test system. The proposed methods are shown to provide significant performance gains relative to the classic matrix and tensor completion based approaches.
Abstract The Escherichia coli genome‐scale metabolic model (GEM) is an exemplar systems biology model for the simulation of cellular metabolism. Experimental validation of model predictions is essential to pinpoint uncertainty and ensure continued development of accurate models. Here, we quantified the accuracy of four subsequent E. coli GEMs using published mutant fitness data across thousands of genes and 25 different carbon sources. This evaluation demonstrated the utility of the area under a precision–recall curve relative to alternative accuracy metrics. An analysis of errors in the latest (iML1515) model identified several vitamins/cofactors that are likely available to mutants despite being absent from the experimental growth medium and highlighted isoenzyme gene‐protein‐reaction mapping as a key source of inaccurate predictions. A machine learning approach further identified metabolic fluxes through hydrogen ion exchange and specific central metabolism branch points as important determinants of model accuracy. This work outlines improved practices for the assessment of GEM accuracy with high‐throughput mutant fitness data and highlights promising areas for future model refinement in E. coli and beyond.
Technological advances and a more engaged customer population are pushing utilities and their regulators towards new strategies that promote growth and transformation. Common to many of these efforts is an interest in expanding the set of profit-generating product and service offerings, hereafter referred to as alternative commercial opportunities, beyond just buying and selling electricity. Prior work has focused on specific categories and types of alternative commercial opportunities and in specific market segments. The report fills an important gap in the literature in two ways. First, we develop a comprehensive taxonomy to categorize the alternative commercial opportunities and provide numerous examples within each category. Second, we identify six issues that regulators may want or need to address when determining if and how investor-owned electric utilities pursue these commercial opportunities. The work is intended to inform regulators and decision-makers about how to navigate these broader reform opportunities, as well as rationalize their response within the context of their state policy strategy and in comparison to their peers in other states.
Lime is typically comprised of calcium carbonate (CaCO 3 ) or calcium magnesium carbonate (CaMg(CO 3 ) 2 ) and is needed to maintain a proper pH in agriculture and forestry soils, but it represents a major cost to growers and results in significant greenhouse gas emissions due to the mining, crushing, and transport required. There is a need to identify existing sources of alkaline mineral wastes and assess their potential as sustainable and cost-effective alternatives to lime. Dregs and grits (DGs) are highly alkaline mineral residues from biomass pulp mills that form during the recovery of pulping chemicals and are mostly comprised of CaCO 3 . For the first time, we assess the efficacy of industrially sourced DGs on 22 acidic soils across the Southeastern United States that are currently used in either agriculture or forestry operations. The application of DGs was found on average to result in the same soil pH response as calcite over multiple soil incubations (0 day to 120 days). An analysis of the carbon content of the soils after the incubation revealed that soils incubated with DGs experienced a statistically significant increase in soil carbon relative to control soils and those incubated with CaCO 3 . The generation and application of DGs emits 0.35 tonnes of CO 2 for every tonne of DGs, which compares favorably to the 0.86 tonnes of CO 2 for every tonne of agricultural lime generated and $85 per tonne lime reported in the literature. DGs prove to be a sustainable and economical substitute for agricultural lime in the acidic soils of the Southeastern United States.
The objective of this work was to develop a first phase consensus roadmap for condition-based qualification (CBQ) of electrical cables. With CBQ, qualification of Class 1E electrical cables moves from a time-based approach to a condition-based approach, which is anticipated to be safer in terms of reliability and conservatism, and more cost effective in the long run. However, due to barriers, the CBQ approach has not yet been adopted by U.S. nuclear power plants (NPPs). Based upon a review of current work evaluating CBQ, the limitation of available condition monitoring technology seems to be the largest barrier. The importance of condition monitoring, or more specifically selecting appropriate condition indicators, during CBQ cannot be understated. However, selecting appropriate condition indicators is challenged by techniques that are destructive and only evaluate cable degradation locally. Further, arguably, no one identified condition indicator fully establishes cable condition. Thus, additional work is necessary to evaluate potential condition indicators towards CBQ. In addition to the requirements of IEC/IEEE Std. 60780-323, ideal condition indicators should include a) both destructive and non-destructive approaches, b) both local and global measurements, c) real-time (i.e., online) monitoring that trends with degradation, d) enable correlation with qualified levels of degradation, and e) be established within a repository of condition indicators with applicable materials and/or components and their acceptance criteria. Additional work is needed in development of technology and methodology prior to adoption of CBQ, especially for extending qualified life of installed components. Education and early experience by the industry and regulators will be required for this change in approach as an alternative to re-analysis. A series of workshops that bring together stakeholders to identify and address gaps will be needed. The longstanding cooperative working group of cable researchers from the U.S. Department of Energy, the Electric Power Research Institute, and the Nuclear Regulatory Commission forms a valuable starting point for development of a consensus roadmap to condition-based qualification approach as a viable options for qualification of cable systems in U.S. light water reactors.
In this report, we describe the predicted impact of large spills or releases of alternative marine fuels. The fuels covered in this report are those that have been identified as potential future fuels for the marine shipping sector by industry experts and government agencies overseeing the development of renewable and low-carbon fuels. Several of these fuels are already in use, such as liquified natural gas, renewable diesel, ethanol, methanol, and biodiesel. Other fuels are hydrogen, dimethyl ether, ammonia, and bio-intermediates, such as catalytic fast pyrolysis biooils and hydrothermal liquefaction bio-crudes. The property databases of these fuels are extensive enough to form predictive assessments. Other potential marine fuels, such as lignin ethanol, have not been extensively evaluated and are therefore not included is this study. For each fuel chemistry, we have surmised the spill profiles and environmental impacts based on existing studies and relevant properties. The technologies used to detect spills (especially those for crude oil detection) are also reviewed for their applicability with alternative fuels, and in some instances, recommendations to improve these technologies for use with a particular fuel chemistry are put forward. Finally, current containment and remediation technologies are reviewed and assessed for their efficacy at handling these alternative fuels.
Resilient operation of interdependent infrastructures against compound hazard events is essential for maintaining societal well-being. To address consequence assessment challenges in this problem space, we propose a novel policy-guided tri-level optimization model applied to a proof-of-concept case study with fuel distribution and transportation networks – encompassing one realistic network; one fictitious, yet realistic network; as well as networks drawn from three synthetic distributions. Mathematically, our approach takes the form of a defender-attacker-defender (DAD) model—a multi-agent tri-level optimization, comprised of a defender, attacker, and an operator acting in sequence. Here, in this study, our notional operator may choose proxy actions to operate an interdependent system comprised of fuel terminals and gas stations (functioning as supplies) and a transportation network with traffic flow (functioning as demand) to minimize unmet demand at gas stations. A notional attacker aims to hypothetically disrupt normal operations by reducing supply at the supply terminals, and the notional defender aims to identify best proxy defense policy options which include hardening supply terminals or allowing alternative distribution methods such as trucking reserve supplies. We solve our DAD formulation at a metropolitan scale and present practical defense policy insights against hypothetical compound hazards. We demonstrate the generalizability of our framework by presenting results for a realistic network; a fictitious, yet realistic network; as well as for three networks drawn from synthetic distributions. Additionally, we demonstrate the scalability of the framework by investigating runtime performance as a function of the network size. Steps for future research are also discussed.
Abstract Microbial lipid metabolism is an attractive route for producing oleochemicals. The predominant strategy centers on heterologous thioesterases to synthesize desired chain-length fatty acids. To convert acids to oleochemicals (e.g., fatty alcohols, ketones), the narrowed fatty acid pool needs to be reactivated as coenzyme A thioesters at cost of one ATP per reactivation - an expense that could be saved if the acyl-chain was directly transferred from ACP- to CoA-thioester. Here, we demonstrate such an alternative acyl-transferase strategy by heterologous expression of PhaG, an enzyme first identified in Pseudomonads , that transfers 3-hydroxy acyl-chains between acyl-carrier protein and coenzyme A thioester forms for creating polyhydroxyalkanoate monomers. We use it to create a pool of acyl-CoA’s that can be redirected to oleochemical products. Through bioprospecting, mutagenesis, and metabolic engineering, we develop three strains of Escherichia coli capable of producing over 1 g/L of medium-chain free fatty acids, fatty alcohols, and methyl ketones.
Here, we improve upon two key aspects of the Menter shear stress transport (SST) turbulence model: (1) We propose a more robust adverse pressure gradient sensor based on the strength of the pressure gradient in the direction of the local mean flow; (2) We propose two alternative eddy viscosity models to be used in the adverse pressure gradient regions identified by our sensor. Direct numerical simulations of the Boeing Gaussian bump are used to identify the terms in the baseline SST model that need correction, and a posteriori Reynolds-averaged Navier-Stokes calculations are used to calibrate coefficient values, leading to a model that is both physics driven and data informed. The two sensor-equipped models are applied to two thick airfoils representative of modern wind turbine applications, the FFA-W3-301 and the DU00-W-212. The proposed models improve the prediction of stall (onset of separation) with respect to the prediction of the baseline SST model.
The E × B staircase is a quasi-periodic pattern of pressure profile corrugations. In this work, we present a new mechanism for E × B staircase formation that involves resonant transport versus non-resonant transport. We start from a potential vorticity evolution system and use quasi-linear theory, a model dispersion relation, and a bi-Lorentzian spectrum approximation, to construct the relation between the fluxes and the profiles. With these fluxes, we close the profile evolution equations and the extended turbulence intensity evolution equation, which together constitute a turbulence-profile evolution system. In this system, the Doppler effect from the E × B mean flow can cause resonance between trapped ion precession motion and the trapped ion mode, which drives a resonant transport contribution to the fluxes. The profiles will be flattened where the resonant transport is switched on. In contrast, for the regions of non-resonant transport, profiles are steeper. A quasi-periodic pattern of profile corrugation (the E × B staircase) spontaneously emerges in this system, which is the two states mentioned above, arranged as alternating layers in space. The feedback processes during the staircase pattern formation are identified. An estimate of the critical value of the boundary heat flux is obtained, above which the staircase formation will be triggered. An estimate scaling of the step size in the staircase pattern is obtained. The resonant turbulent transport is also a mechanism for collisionless saturation of zonal flow. Furthermore, this work is related to internal transport barrier formation and suggests some new scenarios, such as an enhanced confined L mode.