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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Performance Prediction of Big Data Transfer Through Experimental Analysis and Machine Learning

Big data transfer in next-generation scientific ap- plications is now commonly carried out over connections with guaranteed bandwidth provisioned in High-performance Net- works (HPNs) through advance bandwidth reservation. To use HPN resources efficiently, provisioning agents need to carefully schedule data transfer requests and allocate appropriate band- widths. Such reserved bandwidths, if not fully utilized by the requesting user, could be simply wasted or cause extra overhead and complexity in management due to exclusive access. This calls for the capability of performance prediction to reserve bandwidth resources that match actual needs. Towards this goal, we employ machine learning algorithms to predict big data transfer perfor- mance based on extensive performance measurements, which are collected over a span of several years from a large number of data transfer tests using different protocols and toolkits between various end sites on several real-life physical or emulated HPN testbeds. We first identify a comprehensive list of attributes involved in a typical big data transfer process, including end host system configurations, network connection properties, and control parameters of data transfer methods. We then conduct an in-depth exploratory analysis of their impacts on application- level throughput, which provides insights into big data transfer performance and motivates the use of machine learning. We also investigate the applicability of machine learning algorithms and derive their general performance bounds for performance prediction of big data transfer in HPNs. Experimental results show that, with appropriate data preprocessing, the proposed machine learning-based approach achieves 95% or higher pre- diction accuracy in up to 90% of the cases with very noisy real-life performance measurements.

Yun, Daqing↗
DOE OSTI2021

Topographical Controls on Hillslope-Scale Hydrology Drive Shrub Distributions on the Seward Peninsula, Alaska

Observations indicate shrubs are expanding across the Arctic tundra, mainly on hillslopes and primarily in response to climate warming. However, the impact topography exerts on hydrology, nutrient dynamics, and plant growth can make untangling the mechanisms behind shrub expansion difficult. We examined the role topography plays in determining shrub expansion by applying a coupled transect version of a mechanistic ecosystem model (ecosys) in a tundra hillslope site in the Seward Peninsula, Alaska. Modeled biomass of the dominant plant functional types agreed well with field measurements (R 2 = 0.89) and accurately represented shrub expansion over the past 30 years inferred from satellite observations. In the well-drained crest position, canopy water potential and plant nitrogen (N) uptake was modeled to be low from plant and microbial water stress. Intermediate soil water content in the mid-slope position enhanced mineralization and plant N uptake, increasing shrub biomass. The deciduous shrub growth in the mid-slope position was further enhanced by symbiotic N 2 fixation primed by increased root carbon allocation. The gentle slope in the poorly drained lower-slope position resulted in saturated soil conditions that reduced soil O 2 concentrations, leading to lower root O 2 uptake and lower nutrient uptake and plant biomass. Additionally, a simulation that removed topographical interconnectivity between grid cells resulted in (1) a 28% underestimate of mean shrub biomass and (2) over or underestimated shrub productivity at the various hillslope positions. Our results indicate that land models need to account for hillslope-scale coupled surface and subsurface hydrology to accurately predict current plant distributions and future trajectories in Arctic ecosystems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Machine learning to predict final fire size at the time of ignition

Fires in boreal forests of Alaska are changing, threatening human health and ecosystems. Given expected increases in fire activity with climate warming, insight into the controls on fire size from the time of ignition is necessary. Such insight may be increasingly useful for fire management, especially in cases where many ignitions occur in a short time period. Here we investigated the controls and predictability of final fire size at the time of ignition. Using decision trees, we show that ignitions can be classified as leading to small, medium or large fires with 50.4 ± 5.2% accuracy. This was accomplished using two variables: vapour pressure deficit and the fraction of spruce cover near the ignition point. The model predicted that 40% of ignitions would lead to large fires, and those ultimately accounted for 75% of the total burned area. Other machine learning classification algorithms, including random forests and multi-layer perceptrons, were tested but did not outperform the simpler decision tree model. Applying the model to areas with intensive human management resulted in overprediction of large fires, as expected. This type of simple classification system could offer insight into optimal resource allocation, helping to maintain a historical fire regime and protect Alaskan ecosystems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

A General Framework for Error-controlled Unstructured Scientific Data Compression

Data compression plays a key role in reducing storage and I/O costs. Traditional lossy methods primarily target data on rectilinear grids and cannot leverage the spatial coherence in unstructured mesh data, leading to suboptimal compression ratios. We present a multi-component, error-bounded compression framework designed to enhance the compression of floating-point unstructured mesh data, which is common in scientific applications. Our approach involves interpolating mesh data onto a rectilinear grid and then separately compressing the grid interpolation and the interpolation residuals. This method is general, independent of mesh types and typologies, and can be seamlessly integrated with existing lossy compressors for improved performance. We evaluated our framework across twelve variables from two synthetic datasets and two real-world simulation datasets. The results indicate that the multi-component framework consistently outperforms state-of-the-art lossy compressors on unstructured data, achieving, on average, a 2.3 − 3.5× improvement in compression ratios, with error bounds ranging from 1 × 10 the −6 to 1×10−2. We further investigate impact of hyperparameters, such as grid spacing and error allocation, to deliver optimal compression ratios in diverse datasets.

Gong, Qian↗
DOE OSTI2016

Establishing Cost-Effective Allocation of Proton Therapy for Breast Irradiation

Purpose: Cardiac toxicity due to conventional breast radiation therapy (RT) has been extensively reported, and it affects both the life expectancy and quality of life of affected women. Given the favorable oncologic outcomes in most women irradiated for breast cancer, it is increasingly paramount to minimize treatment side effects and improve survivorship for these patients. Proton RT offers promise in limiting heart dose, but the modality is costly and access is limited. Using cost-effectiveness analysis, we provide a decision-making tool to help determine which breast cancer patients may benefit from proton RT referral. Methods and Materials: A Markov cohort model was constructed to compare the cost-effectiveness of proton versus photon RT for breast cancer management. The model was analyzed for different strata of women based on age (40 years, 50 years, and 60 years) and the presence or lack of cardiac risk factors (CRFs). Model entrants could have 1 of 3 health states: healthy, alive with coronary heart disease (CHD), or dead. Base-case analysis assumed CHD was managed medically. No difference in tumor control was assumed between arms. Probabilistic sensitivity analysis was performed to test model robustness and the influence of including catheterization as a downstream possibility within the health state of CHD. Results: Proton RT was not cost-effective in women without CRFs or a mean heart dose (MHD) <5 Gy. Base-case analysis noted cost-effectiveness for proton RT in women with ≥1 CRF at an approximate minimum MHD of 6 Gy with a willingness-to-pay threshold of $100,000/quality-adjusted life-year. For women with ≥1 CRF, probabilistic sensitivity analysis noted the preference of proton RT for an MHD ≥5 Gy with a similar willingness-to-pay threshold. Conclusions: Despite the cost of treatment, scenarios do exist whereby proton therapy is cost-effective. Referral for proton therapy may be cost-effective for patients with ≥1 CRF in cases for which photon plans are unable to achieve an MHD <5 Gy.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2021

Palladium/Ferrierite versus Palladium/SSZ‐13 Passive NOx Adsorbers: Adsorbate‐Controlled Location of Atomically Dispersed Palladium(II) in Ferrierite Determines High Activity and Stability**

Abstract Pd‐loaded FER and SSZ‐13 zeolites as low‐temperature passive NOx adsorbers (PNA) are compared under practical conditions. Vehicle cold start exposes the material to CO under a range of concentrations, necessitating a systematic exploration of the effect of CO on the performance of isolated Pd ions in PNA. The NO release temperature of both adsorbers decreases gradually with an increase in CO concentration from a few hundred to a few thousand ppm. This beneficial effect results from local nano‐“hot spot” formation during CO oxidation. Dissimilar to Pd/SSZ‐13, increasing the CO concentration above ≈1000 ppm improves the NOx storage significantly for Pd/FER, which was attributed to the presence of Pd ions in FER sites that are shielded from NOx. CO mobilizes this Pd atom to the NOx accessible position where it becomes active for PNA. This behavior explains the very high resistance of Pd/FER to hydrothermal aging: Pd/FER materials survive hydrothermal aging at 800 °C in 10 % H 2 O vapor for 16 hours with no deterioration in NOx uptake/release behavior. Thus, by allocating Pd ions to the specific microporous pockets in FER, we have produced (hydro)thermally stable and active PNA materials.

Khivantsev, Konstantin↗
DOE OSTI2021

Palladium/Ferrierite versus Palladium/SSZ-13 Passive NOx Adsorbers: Adsorbate-Controlled Location of Atomically Dispersed Palladium(II) in Ferrierite Determines High Activity and Stability**

Pd-loaded FER and SSZ-13 zeolites as low-temperature passive NOx adsorbers (PNA) are compared under practical conditions. Vehicle cold start exposes the material to CO under a range of concentrations, necessitating a systematic exploration of the effect of CO on the performance of isolated Pd ions in PNA. The NO release temperature of both adsorbers decreases gradually with an increase in CO concentration from a few hundred to a few thousand ppm. This beneficial effect results from local nano-“hot spot” formation during CO oxidation. Dissimilar to Pd/SSZ-13, increasing the CO concentration above ˜1000 ppm improves the NOx storage significantly for Pd/FER, which was attributed to the presence of Pd ions in FER sites that are shielded from NOx. CO mobilizes this Pd atom to the NOx accessible position where it becomes active for PNA. This behavior explains the very high resistance of Pd/FER to hydrothermal aging: Pd/FER materials survive hydrothermal aging at 800°C in 10% H 2 O vapor for 16 hours with no deterioration in NOx uptake/release behavior. Therefore, by allocating Pd ions to the specific microporous pockets in FER, we have produced (hydro)thermally stable and active PNA materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

A genomic perspective on stoichiometric regulation of soil carbon cycling

Similar to plant growth, soil carbon (C) cycling is constrained by the availability of nitrogen (N) and phosphorus (P). We hypothesized that stoichiometric control over soil microbial C cycling may be shaped by functional guilds with distinct nutrient substrate preferences. Across a series of rice fields spanning 5-25% soil C (N:P from 1:12 to 1:70), C turnover was best correlated with P availability and increased with experimental N addition only in lower C (mineral) soils with N:P-1/216. Microbial community membership also varied with soil stoichiometry but not with N addition. Shotgun metagenome data revealed changes in community functions with increasing C turnover, including a shift from aromatic C to carbohydrate utilization accompanied by lower N uptake and P scavenging. Similar patterns of C, N and P acquisition, along with higher ribosomal RNA operon copy numbers, distinguished that microbial taxa positively correlated with C turnover. Considering such tradeoffs in genomic resource allocation patterns among taxa strengthened correlations between microbial community composition and C cycling, suggesting simplified guilds amenable to ecosystem modeling. Our results suggest that patterns of soil C turnover may reflect community-dependent metabolic shifts driven by resource allocation strategies, analogous to growth rate-stoichiometry coupling in animal and plant communities.

58 GEOSCIENCES↗
DOE OSTI2019

Climatic and physiological regulation of the bimodal xylem formation pattern in Pinus pinaster saplings

Abstract Seasonality in tree cambial activity and xylem formation encompass large variation in environmental conditions. Abiotic stressors such as warming or drought also modulate plant behavior at species and individual level. Despite xylem formation susceptibility to carbon (C) and water availability, it is still unknown which are the key physiological variables that regulate xylogenesis, and to what extent plant performance contributes to further explain the number of cells in the different phases of xylem development. Xylogenesis and physiological behavior was monitored in saplings of Pinus pinaster Aiton, a bimodal growth pattern species, distributed in different irrigation regimes. Xylogenesis and plant physiological behavior were compared between treatments and the relationship between climate, physiology and the number of cells in the cambium, enlargement and cell-wall thickening phases was evaluated. Xylogenesis regulation shifted from physiological to climatic control as cell differentiation advanced to mature tracheids. The number of cells in the cambium increased with assimilation rates and decreased with the water potential gradient through the plant. Enlargement was the most susceptible phase to plant relative water content, whereas no physiological variable contributed to explain the number of cells in the wall thickening phase, which declined as temperatures increased. All treatments showed a bimodal growth pattern with a second growth period starting when primary growth was completed and after plants had experienced the highest summer hydraulic losses. Our study demonstrates the importance of including physiological responses and not only climate to fully understand xylogenesis, with special attention to the enlargement phase. This is critical when studying species with a bimodal growth pattern because the second growth peak responds to internal shifts of C allocation and may strongly depend on plant hydraulic responses and not on a fine tuning of cambial activity with soil water availability.

Garcia-Forner, Núria↗
DOE OSTI2018

Optimal subhourly electricity resource dispatch under multiple price signals with high renewable generation availability

This article proposes a system-wide optimal resource dispatch strategy that enables a shift from a primarily energy cost-based approach, to a strategy using simultaneous price signals for energy, power and ramping behavior. A formal method to compute the optimal sub-hourly power trajectory is derived for a system when the price of energy and ramping are both significant. Optimal control functions are obtained in both time and frequency domains, and a discrete-time solution suitable for periodic feedback control systems is presented. The method is applied to North America Western Interconnection for the planning year 2024, and it is shown that an optimal dispatch strategy that simultaneously considers both the cost of energy and the cost of ramping leads to significant cost savings in systems with high levels of renewable generation: the savings exceed 25% of the total system operating cost for a 50% renewables scenario.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Sulfide stress tolerance as a controller of methane production in temperate wetlands

Abstract Wetlands are a major source of methane emissions and contribute to the observed increase in atmospheric methane over the last 20 years. Methane production in wetlands is the final step of carbon decomposition performed by anaerobic archaea. Although hydrogen/carbon dioxide and acetate are the substrates most often attributed to methanogenesis, other substrates—such as methylated compounds—may additionally play important roles in driving methane production in wetland systems. Here we conducted mesocosm experiments combined with genome-resolved metatranscriptomics to investigate the impact of diverse methanogenic substrate amendment on methanogenesis in two high methane-emitting wetlands with distinct geochemistry, termed P7 and P8. Methanol amendment resulted in high methane production at both sites, whereas acetate and formate amendment only stimulated methanogenesis in P7 mesocosms, where aqueous sulfide concentrations were lower. In P7 sediments, formate amendment fueled acetogenic microbes that produced acetate, which was subsequently utilized by acetoclastic methanogens. In contrast to expression profiles in P7 mesocosms, active methylotrophic methanogen genomes from P8 showed increased expression of genes related to membrane remodeling and DNA damage repair, indicative of stress tolerance mechanisms to counter sulfide toxicity. Methylotrophic methanogenesis generates higher free energy yields than acetoclastic methanogenesis, which likely enables allocation of more energy toward stress responses. These findings contribute to the growing body of literature highlighting methylotrophic methanogenesis as an important methane production pathway in wetlands. By using less competitive substrates like methanol that provide greater energy yields, methylotrophic methanogens may invest in physiological strategies that provide competitive advantages across a range of environmental stresses.

Environmental Sciences & Ecology↗
DOE OSTI2023

Revising the dynamic energy budget theory with a new reserve mobilization rule and three example applications to bacterial growth

Dynamic energy budget (DEB) theory has been applied to model a wide range of organisms, including microbes. In the standard DEB model, biomass is partitioned into reserve and structural compartments, where reserve biomass is mobilized in a pseudolinear manner (while the reserve biomass density, defined as the ratio between reserve and structural biomass, decays linearly) to drive maintenance and the growth of structural biomass (and extracellular enzyme production if it is considered). However, the linear dynamics of the reserve biomass density makes the standard DEB model incapable of explaining the slowdown of microbial growth at high reserve density that is caused by macromolecular crowding effect which reduces biochemical reaction rates (a typical situation occurs when microbes are experiencing severe moisture stress) and is inconsistent with the observation that intracellular enzymatic reactions generally follow non-linear kinetics. By partitioning biomass into reserve, kinetic, and structural compartments, we show here that the Equilibrium Chemistry Approximation (ECA) kinetics can be used to represent enzymatically catalyzed reserve biomass mobilization that can then drive the kinetic and structural biomass synthesis. This revised DEB model better represents the tradeoff in ribosome allocation for structural growth and internal enzyme production, is structurally compatible with metabolic models of cell individuals, and includes the standard DEB model and the popular compromise model as special cases for representing population growth. We then applied the revised DEB model to interpret components of bacterial respiration, their dependence on substrate availability, and emergent microbial carbon use efficiency dynamics for an exponentially growing population. We found that the revised DEB model enables a better understanding of bacterial substrates use (carbon in our examples) than that can be derived from a few other models in the literature. In particular, the revised DEB model explains why carbon use efficiency may first increase, then plateau, and finally decrease with growth rate (and substrate uptake rate), as a function of proteomics. Additionally, the revised DEB model explains why the kinetic biomass compartment needs to be divided to reasonably incorporate proteomic control of microbial growth.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

WE-H-BRC-04: Implement Lean Methodology to Make Our Current Process of CT Simulation to Treatment More Efficient

Purpose: Our goal is to implement lean methodology to make our current process of CT simulation to treatment more efficient. Methods: In this study, we implemented lean methodology and tools and employed flowchart in excel for process-mapping. We formed a group of physicians, physicists, dosimetrists, therapists and a clinical physics assistant and huddled bi-weekly to map current value streams. We performed GEMBA walks and observed current processes from scheduling patient CT Simulations to treatment plan approval. From this, the entire workflow was categorized into processes, sub-processes, and tasks. For each process we gathered data on touch time, first time quality, undesirable effects (UDEs), and wait-times from relevant members of each task. UDEs were binned per frequency of their occurrence. We huddled to map future state and to find solutions to high frequency UDEs. We implemented visual controls, hard stops, and documented issues found during chart checks prior to treatment plan approval. Results: We have identified approximately 64 UDEs in our current workflow that could cause delays, re-work, compromise the quality and safety of patient treatments, or cause wait times between 1 – 6 days. While some UDEs are unavoidable, such as re-planning due to patient weight loss, eliminating avoidable UDEs is our goal. In 2015, we found 399 issues with patient treatment plans, of which 261, 95 and 43 were low, medium and high severity, respectively. We also mapped patient-specific QA processes for IMRT/Rapid Arc and SRS/SBRT, involving 10 and 18 steps, respectively. From these, 13 UDEs were found and 5 were addressed that solved 20% of issues. Conclusion: We have successfully implemented lean methodology and tools. We are further mapping treatment site specific workflows to identify bottlenecks, potential breakdowns and personnel allocation and employ tools like failure mode effects analysis to mitigate risk factors to make this process efficient.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Emergent inequality and self-organized social classes in a network of power and frustration

We propose a simple agent-based model on a network to conceptualize the allocation of limited wealth among more abundant expectations at the interplay of power, frustration, and initiative. Concepts imported from the statistical physics of frustrated systems in and out of equilibrium allow us to compare subjective measures of frustration and satisfaction to collective measures of fairness in wealth distribution, such as the Lorenz curve and the Gini index. We find that a completely libertarian, law-of-the-jungle setting, where every agent can acquire wealth from or lose wealth to anybody else invariably leads to a complete polarization of the distribution of wealth vs. opportunity. This picture is however dramatically ameliorated when hard constraints are imposed over agents in the form of a limiting network of transactions. There, an out of equilibrium dynamics of the networks, based on a competition between power and frustration in the decision-making of agents, leads to network coevolution. The ratio of power and frustration controls different dynamical regimes separated by kinetic transitions and characterized by drastically different values of equality. It also leads, for proper values of social initiative, to the emergence of three self-organized social classes, lower, middle, and upper class. Their dynamics, which appears mostly controlled by the middle class, drives a cyclical regime of dramatic social changes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Multi-layered Energy Management Framework for Extreme Fast Charging Stations Considering Demand Charges, Battery Degradation, and Forecast Uncertainties

To achieve a cost-effective and expeditious charging experience for extreme fast charging station (XFCS) owners and electric vehicle (EV) users, the optimal operation of XFCS is crucial. It is however challenging to simultaneously manage the profit from energy arbitrage, the cost of demand charges, and the degradation of a battery energy storage system (BESS) under uncertainties. This paper, therefore, proposes a multi-layered multi-time scale energy flow management framework for an XFCS by considering long- and short-term forecast uncertainties, monthly demand charges reduction, and BESS life degradation. In the proposed approach, an upper scheduling layer (USL) ensures the overall operation economy and yields optimal scheduling of the energy resources on a rolling horizon basis, thereby considering the long-term forecast errors. A lower dispatch layer (LDL) takes the short-term forecast errors into account during the real-time operation of the XFCS. Per the latest research, monthly demand charges can be as high as 90% of the total monthly bills for EV fast charging stations; to this end, this paper takes the first attempt at the reduction of demand charges cost by considering the trade-off between the energy cost and monthly demand charges. Contrasting literature, this work allocates an energy reserve in the BESS stored energy to deal with the impact of short-term forecast errors on the optimized real-time operation of the XFCS. Moreover, degradation modeling considers the trade-off between short-term benefits and long-term BESS life degradation. As a result, case studies and a comparative analysis prove the efficacy of the proposed framework.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Divergence Reduction in Monte Carlo Neutron Transport with On-GPU Asynchronous Scheduling

While Monte Carlo Neutron Transport (MCNT) is near-embarrasingly parallel, the effectively unpredictable lifetime of neutrons can lead to divergence when MCNT is evaluated on GPUs. Divergence is the phenomenon of adjacent threads in a warp executing different control flow paths; on GPUS, it reduces performance because each work group may only execute one path at a time. The process of Thread Data Remapping (TDR) resolves these discrepancies by moving data across hardware such that data in the same warp will be processed through similar paths. A common issue among prior implementations of TDR is the synchronous nature of its remapping and processing cycles, which exhaustively sort data produced by prior processing passes and exhaustively evaluate the sorted data. In another work, we defined a method of remapping data through an asynchronous scheduler which allows for work to be stored in shared memory and deferred arbitrarily until that work is a viable option for low-divergence evaluation. This article surveys a wider set of cases, with the goal of characterizing performance trends across a more comprehensive set of parameters. These parameters include cross sections of scattering/capturing/fission, use of implicit capture, source neutron counts, simulation time spans, and tuned memory allocations. Across these cases, we have recorded minimum and average execution times, as well as a heuristically tuned near-optimal memory allocation size for both synchronous and asynchronous scheduling. Across the collected data, it is shown that the asynchronous method is faster and more memory efficient in the majority of cases, and that it requires less tuning to achieve competitive performance.

Computer Science↗
DOE OSTI2020

Development of a Reference Design for a Cyber-Physical System

The purpose of this thesis is to develop a reference design to assist in the selection of security practices in power electronics design. A prototype will be developed from this reference design for evaluation. This evaluation will include a brief cost/benefit analysis to gauge the efficacy of implementing each layer of security throughout the power electronics design process. This thesis will also describe the obstacles and effectiveness of integrating a Trusted Platform Module (TPM) into a cyber-hardened grid-connected device. The TPM device is a secured crypto processor that assists in generating, storing, and restricting the use of cryptographic keys. The emphasis of this research is to establish integrity, authenticity, and confidentiality within a system by providing a baseline of security concerns for segments of the system. This research considers communication, control, and hardware level securities. The scope of this thesis will review the necessary security methods as well as consider the effects these methods have on the embedded system, to assess the desired security to responsiveness trade off. Applying this approach to a design process will alleviate various unknowns of appending security to a power electronics design. This thesis describes the specific vulnerabilities introduced within this grid-edge environment, and how the liabilities within the system can be mitigated. Initially, common security techniques will be considered to establish a guideline to benchmark performance and resource costs of the system. The foundation will be a non-hardened power electronic system platform with industry standard communication protocols. Several security techniques and attack vectors will then be evaluated to contribute to the base level platform. Other fail-safe features take place to gauge progress of the selected approach, non-inclusive to the TPM. Collectively, this investigation will determine a valid experiment by appraising and categorizing resource allocation, performance overhead, and monetary cost analysis results into a reference design. The prototype will then demonstrate methods to relieve common threats that are purposefully implemented into the design.

Blair, Nicholas Paul↗