Effects of dioxygen pressure on rates of NO[subscript x] selective catalytic reduction with NH[subscript 3] on Cu-CHA zeolites
Abstract not provided
Jones, Casey B.↗
SEARCH · Search NASA
Results for “Rating”
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Electronic impact of Ni2P nanoparticle size on hydrogenation rates
Nickle phosphide, Ni2P, nanoparticles supported on SiO2 show a marked volcano shaped size dependence. Kinetic analysis and physicochemical characterization shows the electron density of Ni to increase with increasing Ni2P size, enhancing in turn the H2 adsorption strength. For particles below 15 nm, H adsorbs weakly causing a low surface coverage of H, gradually increasing with particle size. For large particles, hydrogen binds too strongly causing a high coverage but low catalytic activity. The remarkable size dependence of the electronic properties show that Ni2P particle size can be used to fine-tune its activity for hydrogenation.
Ni2P size effect, Electron density, H2 adsorption ↗
Operando calorimetry informs the origin of rapid rate performance in microwave-prepared TiNb 2 O 7 electrodes
Not Available
Baek, Sun Woong↗
Numerical study of damage in particulate composites during high-strain rate loading using novel damage model
Not provided.
Materials Science↗
Adaptive Data Rate Techniques for Energy Constrained Ad Hoc LoRa Networks.
Abstract not provided.
Heeger, Derek↗
Distributed Control of Charging for Electric Vehicle Fleets Under Dynamic Transformer Ratings
Not provided.
Automation & Control Systems↗
Longwave infrared (6.6–11.4 µm) dual-comb spectroscopy with 240,000 comb-mode-resolved data points at video rate
Using sub-3-cycle pulses from mode-locked Cr:ZnS lasers at λ ≈ 2.4 µm as a driving source, we performed high-resolution dual-frequency-comb spectroscopy in the longwave infrared (LWIR) range. A duo of highly coherent broadband (6.6–11.4 µm) frequency combs were produced via intrapulse difference frequency generation in zinc germanium phosphide (ZGP) crystals. Fast (up to 0.1 s per spectrum) acquisition of 240,000 comb-mode-resolved data points, spaced by 80 MHz and referenced to a Rb clock, was demonstrated, resulting in metrology grade molecular spectra of N 2 O (nitrous oxide) and CH 3 OH (methane). The key to high-speed massive spectral data acquisition was low intensity and phase noise of the LWIR combs and high (7.5%) downconversion efficiency, resulting in a LWIR power of 300 mW for each comb.
Vasilyev, Sergey (ORCID:0000000225203547)↗
Thermodynamically consistent forward and reverse degrees of rate control in reversible reactions
The net rate of a composite reaction is the difference between the forward and reverse reaction rates, which are kinetically distinct despite sharing elementary reaction steps and therefore have different rate-controlling transition states and species. Thus, degrees of rate control defined to identify rate-controlling transition states and species for the net rate confound contributions from the forward and reverse reactions. Herein, the forward and reverse degrees of rate control are defined to independently quantify the extent that species and transition states control the forward and reverse rates in reversible reactions. These degrees of rate control are defined as the relative change in the forward and reverse reaction rates per k B T decrease in the standard-state molecular free energies of transition states and species, and they are related to experimentally measurable quantities such as steady-state fractional coverages, reaction orders, and energies and entropies of activation of the forward and reverse reaction rates. The forward/reverse degrees of rate control represent stoichiometric coefficients for species and transition states in an equilibrium between the apparent initial states and the apparent transition states of the apparent rate-controlling steps of forward and reverse overall reactions. At equilibrium, the apparent transition states for the forward reaction and reverse reaction converge, and thus the forward and reverse rate-controlling steps combine to form a single apparent rate-controlling step at equilibrium. Here, this apparent rate-controlling step is comprised of an apparent initial state, transition state, and final state, where the apparent final state of the forward reaction is the apparent initial state of the reverse reaction. The apparent rate-controlling step behaves identically to an elementary step reaction at equilibrium with a pseudo-mass-action rate function given by the transition-state-theory (TST) form rate function (Foley and Bhan, 2020) with a stoichiometric number equal to the affinity-averaged stoichiometric number, $\bar{σ}$ The ratio of the forward and reverse TST-form rate functions is identical to the overall thermodynamic equilibrium relation, consistent with the principles of microscopic reversibility and detailed balance at equilibrium.
42 ENGINEERING↗
Evaluation of Zero-Net-Rate Pumping Tests
Accurately estimating the distribution of aquifer properties is key to understanding contaminant movement in the subsurface. The distribution of aquifer properties is typically addressed using slug or constant-rate well tests, and the pros and cons of these tests are well known. Slug tests are appealing because they avoid removing contaminated water, but their results are affected by well skin and the small volume of displaced water limits the volume of aquifer that can be evaluated. Constant-rate well tests have the disadvantage of requiring disposal of potentially contaminated water, but they can generate properties that are more representative than slug tests, and they can be used to estimate well efficiency and storativity, which are difficult to characterize using slug tests. Periodic pumping tests are appealing because they have many of the advantages and few of the disadvantages of slug and constant-rate well tests. Periodic pumping tests involve cycling the pumping rate with a regular period and measuring the resulting response in monitoring wells. Some of these tests involve imposing a periodic rate on a constant mean rate. However, other tests involve moving water out and back into the well at rates that are balanced so the net rate after each period is zero. Some zero-net-rate (ZNR) well tests use rates that follow a sinusoidal pattern, whereas others use a square wave pattern that switches between a constant rate of pumping and a constant rate of injection to achieve a zero-net rate. ZNR well tests appear to be a useful compromise between slug and constant rate tests, but methods for conducting and analyzing the results from these tests have received limited evaluation. Periodic pumping tests are typically evaluated through recorded pressure responses to a disturbance source. Recent work has demonstrated that the strain field in the vadose zone shows a response to disturbances in the underlying aquifer. Various instrument designs are available that can record vertical and horizontal strain to very precise resolutions (10-9 ε). Measuring the strain in the vadose zone can present lower costs than measuring pressure in a monitoring well, so using strain could improve the resolution of ZNR tests, as well as make these tests potentially cheaper. A ZNR periodic pumping system was constructed and used to perform tests in the Clemson, South Carolina area. The system was designed to pump and inject with a periodic square-wave, so pumping occurs at a constant rate for half the period and is followed by injection at the same rate for half the period resulting in no net gain or loss of water from the aquifer. The system is designed to generate flow rates from 1 to 3.5 gallons per minute (gpm) with a capacity of 875-gallon per half period. Pressure and strain monitoring points are located in the vicinity of the pumping well. A series of 10 ZNR periodic pumping tests were conducted at the field site, with periods ranging from 2 to 540 minutes. Pressure data were collected and recorded in four monitoring wells in various locations around the pumping well. In addition, vertical and horizontal strain and tilt data were recorded in various locations around the pumping well. Traditional aquifer tests, including slug tests and constant-rate pumping tests were conducted at the field site to provide a baseline of aquifer parameter estimates that are compared the results of ZNR tests. Pressure data measured at monitoring wells during ZNR tests were analyzed utilizing an analytical solution (Streltsova, 1988) that assumes a confined aquifer and estimates hydraulic diffusivity and transmissivity using the time lag and amplitude of the pressure signal. The storativity can be separated out from the hydraulic diffusivity using the transmissivity estimate. The time-lag and amplitude of the pressure signals were estimated using a Fourier transform. The time-lag of the primary period of the pressure increases as a linear function of distance from the pumping well, and it increases as the square root of the period of the ZNR test over a range of periods spanning two orders of magnitudes. The first few harmonics follow similar trends, but the higher frequency harmonics diverge from this trend. Strain and tilt data from various instruments in the vadose and saturated zones are periodic during ZNR tests. The time lags of the strain components increase roughly linearly with distance from the well. Many of the time lags of the strain data from the vadose zone are similar to the time lags observed in the pressure data from a similar distance and pumping period. Theoretical experiments were performed to understand how pressure and strain responds to ZNR periodic pumping. The time-lags of the simulated pressure responses match the field data trends. The results were used to validate the Streltsova (1988) solution for periodic pumping to estimate hydraulic diffusivity. Hydraulic diffusivity was estimated to be 1.8 x 10-2 m2s-1 < Dh < 9.0 x 10-2 m2s-1 using pressure data from all the wells during ZNR tests. Transmissivity was estimated to be 0.8 x 10-4 m2s-1 < T < 4.3 x 10-4 m2s-1. Assuming Storativity = T/Dh gives 1.1 x 10-3 < S < 19 x10-3. Transmissivity is used to estimate the hydraulic conductivity, K, by dividing by the assumed aquifer thickness. Two constant-rate pumping tests were conducted and analyzed using two conceptual models: The Hantush (1961) solution was used to analyze data assuming confined conditions and the Neuman (1974) solution was used to analyze data assuming unconfined conditions. The Hantush (1961) solution estimated transmissivity to be 1.6 x 10-4 m2s-1 < T < 1.8 x 10-4 m2s-1 when using data from all the wells. Storativity was estimated to be 4.4 x 10-3 < S < 8.2 x 10-3. Assuming Dh = T/S gives 0.22 x 10-2 m2s-1 < Dh < 3.6 x 10-2 m2s-1. The Neuman (1974) solution estimated transmissivity to be 0.80 x 10-4 m2s-1 < T < 0.84 x 10-4 m2s-1. Total storativity (S + Sy) was estimated to be 22 x 10-3 < S < 110 x 10-3. Storativity excluding the Sy term was estimated to be 2.2 x 10-3 < S < 2.5 x 10-3. Assuming Dh = T/S gives 0.073 x 10-2 m2s-1 < S < 0.36 x 10-2 m2s-1. Two slug tests were performed on the pumping well, PW-2. The Bouwer and Rice (1976) solution for slug tests was used to analyze the data. This solution works for both confined and unconfined conditions, so both conceptual models were covered through the analysis. Hydraulic conductivity was estimated to be 1.95 x 10-6 ms-1 < K < 2.49 x 10-6 ms-1. Statistical comparison show generally no significant difference in the estimates of Dh, K, or S made using ZNR and conventional pumping tests.. However, the total storage estimated by the Neuman (1974) solution for unconfined settings is larger than that estimate using the Streltsove analysis applied to the ZNR tests. This is likely because the Neuman solution considers delayed yield from storage that the water table, whereas the Streltsova (1988) solution assumes confined conditions. The analysis also indicates that there is a statistically significant difference between parameters estimated with conventional slug tests and those measured with either constant-rate pumping tests or ZNR tests. Hydraulic diffusivity is estimated from the time-lag and the distance from the well. The time-lags of the strain data from the vadose zone are similar to the lags of the pressure data from a similar distance. This indicates that hydraulic diffusivities estimated from the strain data measured in the vadose zone would be similar to the estimates from the pressure data measured in the aquifer. There appear to be sign reversals in some of the strain data that were corrected to estimate the time lag. The dissolved oxygen (CO) concentration was measured during several ZNR tests to evaluate the feasibility of using the procedure to increase contaminant degradation kinetics that are related to DO. The results indicate that DO can be increased during the cycling of ZNR tests in some cases.
Smith-Jones, Austin↗
Disaggregating Future Retail Electricity Rate Growth [Slides]
Recent Berkeley Lab research found that modest retail rate increases over the past 10 years were mostly driven by large increases in capital expenditures (CapEx) that were offset in part by substantial wholesale price reductions. Decision-makers are increasingly concerned about the potential future rate impacts of a number of policies and industry trends that support rapid decarbonization, electrification, and grid modernization. Using historical FERC Form 1 data and the existing literature on policies and industry trends that are likely to affect utility-incurred costs and retail sales, Berkeley Lab researchers developed ranges of forecasted growth rates for cost-related rate drivers (i.e., fuel and purchased power; transmission, distribution, generation, and other categories of both non-fuel operations & maintenance and CapEx) and non-cost related rate drivers (i.e., retail sales, peak demand, and customers). These were then used as inputs to a pro-forma utility financial model (FINDER) that estimated the growth in retail electric rates between 2020 and 2030 for a prototypical vertically-integrated investor-owned utility in the United States. The analysis produced the following results: 1. Assuming average growth rates in all rate drivers, future retail rate growth is driven by sizable increases in all CapEx costs, where fuel and purchased power costs are replaced by generation CapEx as the largest rate component between 2020 and 2030. 2. Growth in sales/peak demand/customers, generation CapEx costs, and fuel and purchased power (FPP) costs, in isolation, produce the most uncertainty in rate growth. Specifically, a 1% increase in the compound annual growth rate (CAGR) of retail sales, coincident peak demand (CP), and customers (Sales-CP-Cust) results in a 0.88-0.93% decrease in the CAGR of rates, in isolation. However, a 1% increase in the CAGR of generation CapEx budgets results in a 0.07-0.14% increase in the CAGR of rates, while a 1% increase in the CAGR of FPP costs causes a 0.10-0.14% increase in the CAGR of rates, all else being equal. 3. Taking into account the correlation and variability of the growth in all rate drivers jointly, generation CapEx is expected to be both the largest and most uncertain rate component by 2030 (20-25% share of the retail rate). Transmission and distribution CapEx, along with fuel and purchased power costs are each expected to comprise between 12% and 17% of retail rates.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Progressing Analysis of Variable Electric Rates (PAVER) Study
The Progressing Analysis of Variable Electric Rates (PAVER) study analyzed the impact of a range of time-varying electric rates on the performance of a regional electric grid and the resulting costs for participating and non-participating customers. This analysis leveraged and extended the work of PNNL’s Distribution System Operator with Transactive (DSO+T) study. Five different rate designs were included: a flat volumetric energy charge, a typical Time of Use (TOU) rate, a dynamic energy (DE) rate (based on wholesale locational marginal prices), a dynamic energy and capacity (DE+C) rate, and, finally, a Block and Swing (B&S) rate that billed customers based on their average load profile at constant pricing, but used the DE+C dynamic price for load deviations from their average profile. These rates were analyzed in a large-scale co-simulation of an entire regional grid with a customer population representative of the current state. A large fraction (80%) of residential and commercial customers were assumed to participate in these time-varying rates with automatically controlled HVAC, water heaters, electric vehicles, and batteries. This study assumed no industrial sector participation. The DE and DE+C rates saw system peak loads reduced by 6-7%, while the large participation in the TOU rate case saw a significant rebound effect and a resulting peak load increase of >5%. The impacts to the annual and peak system demand impacted system wholesale prices and the overall grid operating costs. This cost structure determined the revenue needed to be collected from customers by each rate design. Participating customers on the DE and DE+C rates (located in one of the modeled DSOs) saw reductions in average annual electricity bills of 11-17% with average increases in monthly bill variation of no more than 13%. At such high participation levels, TOU customers saw 10% higher average annual bills (due to system-wide rebound effects) and average increased monthly bill variation of 16%. Residential owners of large flexible loads (such as electric vehicles) saw larger bill savings (17-20%) when on a fully dynamic rate. The presence of on-site generation (such as rooftop solar) did not appear to appreciably change customer outcomes. Customers on the Block and Swing rate did see 6% lower monthly bill variation (as intended) than the flat rate case, but at the expense of appreciable bill savings, which were only 3%, comparable to the savings seen by non-participants. Given this finding we recommend that additional research be conducted into how best various bill protection mechanisms can balance minimizing customer bill variation with providing financial incentives commensurate with the flexibility customers provide. We also recommend that customer outcomes be explored across a range of regions using current actual customer and system cost data.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗