Research
Research
Embedded Files
Instrumentation
Instrumentation
2025 Summer @BNL
2025 Summer @BNL
Ongoing research at Brookhaven National Lab's instrumentation division:
Developing calibration system for RF instruments.
AAS_Presentation.mp4The audio in this video was for my iPoster presented at AAS 241. IPoster can be found here.
FPGA Design with the Red Pitaya: Developing a spectrometer for H1 Observations
FPGA Design with the Red Pitaya: Developing a spectrometer for H1 Observations
Space contains clouds of neutral Hydrogen, which emits a radio frequency signal when in a higher energy configuration. The signal emitted by neutral Hydrogen can help us understand how galaxies move, map the Milky Way galaxy, and survey RFI in urban areas. CHART encourages citizen science while measuring this natural phenomenon by building a radio telescope for no more than $300.
RTL-Software-Defined Radio (SDR) has a sampling rate of 3.2 Msps. This limits the bandwidth of the receiver. The goal is to increase the sampling rate to collect more data and therefore more accurately measure the environment around the 21-cm line.
As a result of developing a Spectrometer as a backend for CHART using Red Pitaya's FPGA capabilities, the sampling rate was increased from 3.2 Msps to 125 Msps. In-lab tests accurately detected tones generated in the lab with an RF transmitter at various distances ranging from 27 inches to approximately 15 feet.
Modeling
Modeling
Algae under attack: Mathematical modeling of temporal population dynamics between biofuel-relevant microalgae and predatory bacteria
Algae under attack: Mathematical modeling of temporal population dynamics between biofuel-relevant microalgae and predatory bacteria
In 2019 the Energy Information Administration reported that over 70% of our Energy is sourced from coal, natural gas, and petroleum. As the Department of Energy works towards renewable energy it has implemented research in carbon capture technologies and renewable energies like biofuels. The efforts to move towards renewable energy have led to research in microalgal ponds to harvest algal byproducts used in biofuel cultivation.
The objective: to develop a mathematical model that can: Inform us of when a crash is likely to happen and fits our experimental data.
As a result of mathematically modeling the interactions between algicidal bacteria and biofuel-relevant algae using the traditional Predator-Prey model, the values did not fit the trajectory shown in Figure 1. The parameter values were then optimized using the Nelder-Mead method, which minimized error. The optimized parameters in the mathematical model resulted in a more accurate prediction of the interactions.
FinalRecording_DianaMorales_SLAM.mp4mmWave Radar
mmWave Radar
WDE_Poster_Diana_Morales_SULI.pdfPage updated
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